CN114580759A - Urban low-carbon emission reduction evaluation system - Google Patents
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Abstract
The invention provides an urban low-carbon emission reduction evaluation system, which comprises: an acquisition module: the system is used for acquiring and collecting parameter indexes of a target city; wherein the parameter indicators include at least a driving force indicator, a pressure indicator, a response indicator, a status indicator, and an influence indicator; an evaluation index system module: the method comprises the steps of selecting an evaluation index according to a preset low-carbon emission reduction standard criterion, and establishing an evaluation index system according to the evaluation index; an evaluation module: and the evaluation index system is used for evaluating the parameter index based on the evaluation index system and generating an evaluation result.
Description
Technical Field
The invention relates to the technical field of low carbon emission reduction, energy conservation and environmental protection, in particular to an urban low carbon emission reduction evaluation system.
Background
At present, the urban low carbon emission reduction evaluation method is an application of multi-index comprehensive evaluation, but the existing low carbon emission reduction evaluation method is not perfect and comprehensive, the source of carbon emission often has many uncertain factors and changes, an evaluation model utilizes a single evaluation mode, and often has a large error with the obtained data.
Disclosure of Invention
The invention provides an urban low-carbon emission reduction evaluation system to solve the problems.
The invention provides an urban low-carbon emission reduction evaluation system which is characterized by comprising the following components:
an acquisition module: the method comprises the steps of acquiring and collecting parameter indexes of a target city based on a preset DPSIR model; wherein, the first and the second end of the pipe are connected with each other,
the parameter indexes at least include a driving force index, a pressure index, a response index, a state index and an influence index;
an evaluation index system module: the method comprises the steps of selecting an evaluation index through a preset standard criterion and parameter index of low carbon emission reduction, and establishing an evaluation index system through the evaluation index;
an evaluation module: the evaluation index system is used for evaluating the parameter index based on the evaluation index system and generating an evaluation result;
an optimization module: and the system is used for carrying out diagnosis and analysis on the evaluation result, generating optimized data and optimizing an evaluation index system through the optimized data.
As an embodiment of the present technical solution, the acquisition module includes:
class classification index system unit: the system is used for acquiring carbon related indexes of a target city based on a preset DPSIR model, classifying the carbon related indexes of the target city and constructing an equal class classification index system;
carbon emission index unit: the system is used for analyzing and grading the classification index systems based on a preset fuzzy mathematical method, and determining carbon emission indexes;
a parameter index unit: and the system is used for acquiring and collecting the parameter index of the target city through the carbon emission index.
As an embodiment of the present technical solution, the class classification index system unit includes:
DPSIR model subunit: the method comprises the steps of acquiring a driving force index, a pressure index, a response index, a state index and an influence index of urban carbon emission based on a preset DPSIR model; wherein the content of the first and second substances,
the driving force index comprises a carbon emission index of social and economic activities and industrial development;
the pressure index comprises a carbon emission index of resource energy consumption and environmental pollution emission;
the response indicator comprises a carbon emission reduction response indicator;
the state indexes comprise carbon emission indexes of change of the ecological system state and the environmental state;
the influence indexes comprise environmental change results and carbon emission indexes of social and economic influences;
contrast matrix subunit: the method is used for analyzing the relation among all indexes based on a preset analytic hierarchy process, and establishing a contrast matrix through the relation;
class classification index system subunit: and the method is used for classifying all indexes through the comparison matrix and constructing an equal class classification index system.
As an embodiment of the present invention, the carbon emission index unit includes:
carbon source discharge subunit: the method is used for analyzing indexes in a peer classification index system through a preset principal component analysis method and determining a carbon emission source;
a statistics result subunit: the device is used for clustering and counting the carbon emission sources through a preset fuzzy clustering method and a multivariate statistical method, and determining a statistical result;
class classification index system subunit: the method is used for carrying out hierarchical analysis on the statistical result based on a preset triangular fuzzy hierarchical analysis method and constructing an equal-class hierarchical index system;
carbon rejection indicator subunit: the system is used for determining the carbon emission index through the class grading index system.
As an embodiment of the present technical solution, the equal class classification index system subunit is configured to classify all the indexes through the comparison matrix, and construct an equal class classification index system, further including:
establishing a corresponding variable measurement error model based on the comparison matrix;
wherein S is a contrast matrix, IsIs a coefficient matrix related to the contrast matrix, x is a parameter estimation vector related to the contrast matrix, E is an identity matrix, F represents an observation error value of the contrast matrix, D represents a structure matrix, VSRepresenting the correction vector with respect to the contrast matrix, vec (I)s) Representing the coefficient matrix IsDrawn into a sum VSThe vectors of equal length are used as vectors,
a set of parametric measurement vectors representing the contrast matrix,
representing a set of variable floating ranges for the parameter estimate vectors, L representing a model of variable measurement errors for the contrast matrix;
performing parameter estimation through the variable measurement error model to determine an error parameter matrix;
wherein the content of the first and second substances,
representing an error parameter matrix, i representing the iteration times of parameter estimation calculation of the variable measurement error model, and H representing a structural objective function preset about a correction vector; t represents a device, and k represents a Lagrangian constant vector;
represents a set of parameter estimate vectors after i iterative computations,
represents a variable floating range set k after i +1 iterative computationsi+1Representing the Lagrange constant vector after i +1 times of iterative computation;
calculating the error parameter matrix according to preset iteration times, determining an error iteration value, judging whether the error iteration value is greater than a preset classification error threshold value or not, and determining a judgment result;
when the judgment result is greater than or equal to a preset classification error threshold value, adding 1 to the number of the existing index types, classifying the corresponding indexes into a new type, and automatically calculating the next index;
when the judgment result is smaller than a preset classification error threshold value, classifying the corresponding index into the currently calculated index type, and automatically calculating the next index;
and when all the indexes are classified, generating a classification result, and constructing an equal class classification index system according to the classification result.
As an embodiment of the present technical solution, the DPSIR model subunit collects a driving force index, a pressure index, a response index, a state index, and an influence index of urban carbon emission based on a preset DPSIR model, and further includes:
acquiring acquisition requirements of different indexes based on a preset DPSIR model;
compiling an automatic acquisition task based on the acquisition requirement; wherein the content of the first and second substances,
the automatic acquisition task comprises a task name, a task type, an acquisition group and an acquisition data item;
acquiring carbon related indexes of a target city through the automatic acquisition task, and recording acquisition task information; wherein the content of the first and second substances,
the collection task information at least comprises task execution starting and ending time, a collection period, execution priority and normal collection times.
As an embodiment of the present technical solution, the evaluation index system module includes:
primary evaluation index system unit: the system is used for carrying out frequency analysis on the parameter indexes through a preset low-carbon emission reduction standard criterion and establishing a primary evaluation index system;
a research and screening unit: the system is used for researching and screening the primary evaluation index system and calculating the index weight of each index in the primary evaluation index system;
a low carbon emission reduction status unit: the system is used for sequencing the index weights based on a preset fuzzy comprehensive evaluation system to determine the low-carbon emission reduction condition;
an index attribute unit: the method comprises the steps of obtaining relevant threshold values and parameters of the low-carbon emission reduction condition, and analyzing index attributes according to the relevant threshold values and parameters; wherein the content of the first and second substances,
the index attributes comprise a forward index attribute and a reverse index attribute;
evaluation index system unit: and the evaluation index system is constructed according to the index attribute and the primary evaluation index system.
As an embodiment of the present technical solution, the low carbon emission reduction situation unit includes:
a weighting indicator subunit: the system is used for acquiring the index weights, weighting each index weight and determining a weighted index;
average indicator subunit: the weighting indexes are averaged to determine an average index;
the comprehensive evaluation value subunit: the method is used for evaluating the average index based on a preset fuzzy comprehensive evaluation system average to obtain a comprehensive evaluation value;
a low carbon emission reduction status subunit: and the low-carbon emission control system is used for sequencing the low-carbon emission of different areas according to the magnitude of the evaluation value and analyzing the low-carbon emission reduction condition.
As an embodiment of the present technical solution, the index attribute unit is configured to obtain a relevant threshold and a parameter of the low carbon emission reduction condition, and further includes:
acquiring a preset urban carbon emission standard based on a preset big data center, and calculating an allowable value of a relevant index of low carbon emission reduction;
calculating a carbon emission saturation value of the target city according to the allowable value, and determining a moderate value of a relevant index of low carbon emission reduction;
obtaining subjective weight and objective weight, and calculating a satisfaction value of related indexes of low carbon emission reduction;
determining relevant thresholds and parameters according to the fitness value, the impermissible value and the satisfaction value.
As an embodiment of the present technical solution, the optimization module includes:
an evaluation score unit: the system is used for receiving the evaluation result and generating a corresponding evaluation score based on a preset evaluation mechanism;
an analysis result unit: the evaluation score is analyzed and diagnosed based on a preset big data processing center to generate an analysis result;
learning data unit: the system is used for digitizing the analysis result, performing feature extraction and learning on the analysis result, and training corresponding learning data;
optimizing a data unit: for generating corresponding optimized data based on the learning data;
an optimization unit: and the evaluation index system is optimized through the optimization data.
The invention has the following beneficial effects: the technical scheme provides an urban low-carbon emission reduction evaluation system which comprises an acquisition module, an evaluation index system module, an evaluation module and an optimization module; comprehensively evaluating the carbon emission reduction of a target city. The acquisition module is used for acquiring and acquiring parameter indexes of a target city based on a preset DPSIR model, wherein the DPSIR model comprises driving force, pressure, state, influence and response, and the driving force refers to social and economic development and corresponding life consumption modes and production forms; pressure refers to the operation and discharge of the relevant chemical and biological mechanisms, as well as the use of land and other resources, etc.; the state refers to the quantity and quality of physical, biological and chemical phenomena in a specific area and time, and is represented as the condition of a city under the action of pressure; the influence means that data causing the change of the environmental factors are provided, namely, the influence on urban resource environment, social economy and human life is exerted; responses refer to countermeasures taken by governments, systems, people and individuals involved in preventing, reducing, mitigating, and accommodating environmental changes; the evaluation index system module is used for selecting an evaluation index through presetting a standard criterion and a parameter index of low carbon emission reduction, and establishing an evaluation index system through the evaluation index; the evaluation module is used for evaluating the parameter indexes based on an evaluation index system and generating evaluation results, the optimization module carries out diagnosis and analysis on the evaluation results and generates optimized data, and the evaluation index system is optimized through the optimized data, so that the robustness and the self-adaptability of the evaluation index system of the technical scheme are met.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
FIG. 1 is a system block diagram of an urban low carbon emission reduction assessment system according to an embodiment of the present invention;
FIG. 2 is a system block diagram of an urban low carbon emission reduction assessment system according to an embodiment of the present invention;
fig. 3 is a system block diagram of an urban low carbon emission reduction evaluation system in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it should be understood that they are presented herein only to illustrate and explain the present invention and not to limit the present invention.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly or indirectly connected to the other element.
It is to be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in an orientation or positional relationship indicated in the drawings for convenience in describing the invention and to simplify the description, and are not intended to indicate or imply that the device or element so referred to must be in a particular orientation, constructed or operated in a particular orientation, and is not to be construed as limiting the invention.
Moreover, it is noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions, and "a plurality" means two or more unless specifically limited otherwise. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Example 1:
as shown in fig. 1, an embodiment of the present invention provides an urban low carbon emission reduction evaluation system, which is characterized by including:
an acquisition module: the method comprises the steps of acquiring and collecting parameter indexes of a target city based on a preset DPSIR model; wherein, the first and the second end of the pipe are connected with each other,
the parameter indexes include at least a driving force index, a pressure index, a response index, a state index and an influence index;
evaluation index system module: the method comprises the steps of selecting an evaluation index through a preset standard criterion and parameter index of low carbon emission reduction, and establishing an evaluation index system through the evaluation index;
an evaluation module: the evaluation index system is used for evaluating the parameter index based on the evaluation index system and generating an evaluation result;
an optimization module: and the system is used for carrying out diagnostic analysis on the evaluation result, generating optimized data and optimizing an evaluation index system through the optimized data.
The working principle and the beneficial effects of the technical scheme are as follows:
the technical scheme provides an urban low-carbon emission reduction evaluation system which comprises an acquisition module, an evaluation index system module, an evaluation module and an optimization module; comprehensively evaluating the carbon emission reduction of a target city. The acquisition module is used for acquiring and acquiring parameter indexes of a target city based on a preset DPSIR model, wherein the DPSIR model comprises driving force, pressure, state, influence and response, and the driving force refers to social and economic development and corresponding life consumption modes and production forms; pressure refers to the operation and discharge of the relevant chemical and biological mechanisms, as well as the use of land and other resources, etc.; the state refers to the quantity and quality of physical, biological and chemical phenomena in a specific area and time, and is represented as the condition of a city under the action of pressure; the influence means that data causing the change of the environmental factors are provided, namely, the influence on urban resource environment, social economy and human life is exerted; responses refer to countermeasures taken by governments, systems, people and individuals involved in preventing, reducing, mitigating, and accommodating environmental changes; the evaluation index system module is used for selecting an evaluation index through presetting a standard criterion and a parameter index of low carbon emission reduction, and establishing an evaluation index system through the evaluation index; the evaluation module is used for evaluating the parameter indexes based on an evaluation index system and generating evaluation results, the optimization module carries out diagnosis and analysis on the evaluation results and generates optimized data, and the evaluation index system is optimized through the optimized data, so that the robustness and the self-adaptability of the evaluation index system of the technical scheme are met.
Example 2:
as shown in fig. 2, the present technical solution provides an embodiment, where the acquisition module includes:
class classification index system unit: the system is used for acquiring carbon related indexes of a target city based on a preset DPSIR model, classifying the carbon related indexes of the target city and constructing an equal class classification index system;
carbon emission index unit: the system is used for analyzing and grading the classification index systems based on a preset fuzzy mathematical method, and determining the carbon emission index;
a parameter index unit: and the system is used for acquiring and collecting the parameter index of the target city through the carbon emission index.
The working principle and the beneficial effects of the technical scheme are as follows:
the acquisition module of the technical scheme comprises an equal class classification index system unit, a carbon discharge index unit and a parameter index unit; the equal class classification index system unit is used for classifying carbon related indexes of a target city based on a preset DPSIR model, constructing an equal class classification index system, classifying different carbon emission source types so as to facilitate data calculation and statistics, the carbon emission index unit is used for analyzing and grading the equal class classification index system based on a preset fuzzy mathematical method, determining carbon emission indexes, grading different carbon emission sources and obtaining a main carbon emission source in each index in the DPSIR model, the DPSIR model is an evaluation index system conceptual model widely used in an environmental system, is an index system for measuring environment and sustainable development, considers the carbon environment from the perspective of system analysis, and divides the evaluation index of a natural system into a Driving force (Driving force), a Pressure (Pressure), an influence (Impact), a State (State) and a response (Responses), wherein each type comprises a plurality of indexes, the parameter index unit is used for obtaining and collecting parameter indexes of a target city through the carbon discharge indexes so as to obtain comprehensive evaluation parameter indexes, linear causal relationships in the DPSIR model simplify complex carbon discharge calculation problems, and the DPSIR can be used as a useful classification method for summarizing and synthesizing obtained information in strategic environment evaluation to avoid the carbon discharge indexes so as to form an early warning guiding type environment protection mechanism.
Example 3:
as shown in fig. 3, the present technical solution provides an embodiment, where the class classification index system unit includes:
DPSIR model subunit: the system comprises a data acquisition unit, a data processing unit and a data processing unit, wherein the data acquisition unit is used for acquiring a driving force index, a pressure index, a response index, a state index and an influence index of urban carbon emission based on a preset DPSIR model; wherein the content of the first and second substances,
the driving force index comprises a carbon emission index of social and economic activities and industrial development;
the pressure index comprises a carbon emission index of resource energy consumption and environmental pollution emission;
the response indicator comprises a carbon emission reduction response indicator;
the state indexes comprise carbon emission indexes of change of the ecological system state and the environmental state;
the influence indexes comprise environmental change results and carbon emission indexes of social and economic influences;
contrast matrix subunit: the method is used for analyzing the relation among all indexes based on a preset analytic hierarchy process, and establishing a contrast matrix through the relation;
class classification index system subunit: and the system is used for classifying all indexes through the comparison matrix and constructing an equal class classification index system.
The working principle and the beneficial effects of the technical scheme are as follows:
the DPSIR model subunit of the technical scheme is used for acquiring a driving force index, a pressure index, a response index, a state index and an influence index of urban carbon emission based on a preset DPSIR model; the driving force index comprises a carbon emission index of social and economic activities and industrial development; the pressure index comprises the carbon emission index of resource energy consumption and environmental pollution emission; the response index comprises a carbon emission reduction response index; the state indexes comprise carbon emission indexes of change of the ecological system state and the environmental state; the influence indexes comprise environmental change results and carbon emission indexes influenced by social economy; the contrast matrix subunit is used for analyzing the relation among all indexes based on a preset analytic hierarchy process, and establishing a contrast matrix through the relation; and the class classification index system subunit is used for classifying all indexes through the comparison matrix and constructing a class classification index system. The effectiveness and feasibility of the algorithm are verified through analysis and comparison.
Example 4:
this technical scheme provides an embodiment, arrange carbon index unit includes:
carbon source discharge subunit: the method is used for analyzing indexes in a peer classification index system through a preset principal component analysis method and determining a carbon emission source;
a statistics result subunit: the device is used for clustering and counting the carbon emission sources through a preset fuzzy clustering method and a multivariate statistical method, and determining a statistical result;
class classification index system subunit: the method is used for carrying out hierarchical analysis on the statistical result based on a preset triangular fuzzy hierarchical analysis method and constructing an equal-class hierarchical index system;
carbon rejection indicator subunit: the system is used for determining the carbon emission index through the class grading index system.
The working principle and the beneficial effects of the technical scheme are as follows:
the carbon emission index unit of the technical scheme comprises a carbon emission source subunit, a statistical result subunit, an equal class classification index system subunit and a carbon emission index subunit, wherein the carbon emission index subunit is used for analyzing and classifying the equal class classification index system based on a preset fuzzy mathematical method to determine a carbon emission index and classify carbon emission sources from different sources so as to facilitate calculation and statistics of subsequent modules, the carbon emission source subunit is used for analyzing indexes in the equal class classification index system by a preset principal component analysis method to determine a carbon emission source, and planning principal components so as to obtain the carbon emission source with data exceeding a certain amount, roughly or not counting the data with the very little carbon emission source, so that the statistical efficiency of the data is improved, and the statistical result subunit is used for calculating the carbon emission source by a preset fuzzy clustering method and a multivariate statistical method, clustering and counting carbon emission sources, determining a statistical result, counting the carbon emission sources, and carrying out an equal class grading index system subunit for carrying out hierarchical analysis on the statistical result and constructing an equal class grading index system based on a preset triangular fuzzy hierarchical analysis method; and the carbon discharge index subunit is used for determining the carbon discharge index through an equal classification index system.
Example 5:
the technical scheme provides an embodiment, the method for acquiring the driving force index, the pressure index, the response index, the state index and the influence index of urban carbon emission based on a preset DPSIR model further comprises the following steps:
acquiring acquisition requirements of different indexes based on a preset DPSIR model;
compiling an automatic acquisition task based on the acquisition requirement; wherein, the first and the second end of the pipe are connected with each other,
the automatic acquisition task comprises a task name, a task type, an acquisition group and an acquisition data item;
acquiring carbon related indexes of a target city through the automatic acquisition task, and recording acquisition task information; wherein the content of the first and second substances,
the collection task information at least comprises task execution starting and ending time, a collection period, execution priority and normal collection times.
The working principle and the beneficial effects of the technical scheme are as follows:
the acquisition module of the technical scheme acquires driving force indexes, pressure indexes, response indexes, state indexes and influence indexes of urban carbon emission based on a preset DPSIR model, can count the carbon emission in a closed-loop response mode from a causal relationship through the DPSIR model, not only can divide the indexes, but also improves the dividing efficiency of the indexes, and simultaneously acquires the acquisition requirements of different indexes based on the preset DPSIR model; the method comprises the steps of collecting carbon related indexes of a target city through an automatic collection task, recording collection task information, and counting the workload of carbon emission, wherein the collection task information at least comprises task execution starting and ending time, a collection period, execution priority and normal collection times, so that the carbon emission indexes of the city are comprehensively and accurately counted.
Example 6:
the technical solution provides an embodiment, wherein the evaluation index system module includes:
primary evaluation index system unit: the system is used for carrying out frequency analysis on the parameter indexes through a preset low-carbon emission reduction standard criterion and establishing a primary evaluation index system;
a research and screening unit: the system is used for researching and screening the primary evaluation index system and calculating the index weight of each index in the primary evaluation index system;
a low-carbon emission reduction condition unit: the system is used for sequencing the index weights based on a preset fuzzy comprehensive evaluation system to determine the low-carbon emission reduction condition;
an index attribute unit: the method comprises the steps of obtaining relevant thresholds and parameters of the low-carbon emission reduction condition, and analyzing index attributes according to the relevant thresholds and parameters; wherein the content of the first and second substances,
the index attributes comprise a forward index attribute and a reverse index attribute;
evaluation index system unit: and the evaluation index system is constructed according to the index attribute and the primary evaluation index system.
The working principle and the beneficial effects of the technical scheme are as follows:
the evaluation index system module comprises a primary evaluation index system unit, a research and screening unit, a low-carbon emission reduction condition unit and an index attribute unit; the primary evaluation index system unit is used for carrying out frequency analysis on the existing parameter indexes through presetting a standard criterion of low carbon emission reduction, and establishing a primary evaluation index system; the frequency analysis is used for carrying out frequency calculation through the weight and extracting the priority and the importance of evaluation, and the investigation and screening unit is used for carrying out investigation and screening on a primary evaluation index system and calculating the weight of each index in the primary evaluation index system; the low carbon emission reduction condition unit is used for carrying out weighted average on each index weight through the index weight to obtain a comprehensive evaluation value, analyzing the low carbon emission reduction condition according to the evaluation value, and subjectively and observably synthesizing the low carbon emission reduction condition through the investigation and screening unit and the low carbon emission reduction condition unit to facilitate the environmental protection strategy; the index attributes comprise a forward index attribute and a reverse index attribute, the higher the forward index attribute is, the less the representative carbon emission is, the higher the reverse index attribute is, the more the representative carbon emission is, the evaluation index system unit is used for constructing an evaluation index system according to the index attributes and a primary evaluation index system,
example 7:
the technical scheme provides an embodiment, and the low-carbon emission reduction condition unit comprises:
a weighting indicator subunit: the system is used for acquiring the index weights, weighting each index weight and determining a weighted index;
average indicator subunit: the weighting indexes are averaged to determine an average index;
the comprehensive evaluation value subunit: the method is used for evaluating the average index based on a preset fuzzy comprehensive evaluation system average to obtain a comprehensive evaluation value;
a low carbon emission reduction status subunit: and the low-carbon emission control system is used for sequencing the low-carbon emission of different areas according to the magnitude of the evaluation value and analyzing the low-carbon emission reduction condition.
The working principle and the beneficial effects of the technical scheme are as follows:
in the evaluation index system module of the technical scheme, the primary evaluation index system unit is used for carrying out frequency analysis on the parameter indexes through presetting a standard criterion of low carbon emission reduction to establish a primary evaluation index system; the investigation and screening unit is used for carrying out investigation and screening on the primary evaluation index system and calculating the index weight of each index in the primary evaluation index system; the low-carbon emission reduction condition unit is used for sequencing the index weights based on a preset fuzzy comprehensive evaluation system and determining a low-carbon emission reduction condition; the index attribute unit is used for acquiring related threshold values and parameters of the low-carbon emission reduction condition and analyzing the index attributes according to the related threshold values and parameters; the index attributes comprise a forward index attribute and a reverse index attribute; and the evaluation index system unit is used for constructing an evaluation index system according to the index attribute and the primary evaluation index system.
Example 8:
the technical scheme provides an embodiment, and the low carbon emission reduction condition unit comprises:
a weighting indicator subunit: the system is used for acquiring the index weights, weighting each index weight and determining a weighted index;
average indicator subunit: the weighting indexes are averaged to determine an average index;
the comprehensive evaluation value subunit: the method is used for evaluating the average index based on a preset fuzzy comprehensive evaluation system average to obtain a comprehensive evaluation value;
a low carbon emission reduction status subunit: and the low-carbon emission control system is used for sequencing the low-carbon emission of different areas according to the magnitude of the evaluation value and analyzing the low-carbon emission reduction condition.
The working principle and the beneficial effects of the technical scheme are as follows:
the technical scheme provides an embodiment, and the low carbon emission reduction condition unit comprises: the weighting index subunit is used for acquiring the index weights, weighting each index weight and determining a weighting index; the average index subunit is configured to average the weighted indexes to determine an average index; the comprehensive evaluation value subunit is used for evaluating the average index based on a preset fuzzy comprehensive evaluation system average to obtain a comprehensive evaluation value; the low carbon emission reduction status subunit is used for sequencing the low carbon emissions in different areas according to the evaluation value, analyzing the low carbon emission reduction status, performing regional analysis on the carbon emissions in different areas, and analyzing the local carbon emission situation from the aspects of industrial, human and environmental factors based on local regional factors.
Example 9:
the technical scheme provides an embodiment, wherein the index attribute unit is used for acquiring relevant thresholds and parameters of the low-carbon emission reduction condition, and further comprises:
acquiring a preset urban carbon emission standard based on a preset big data center, and calculating an allowable value of a relevant index of low carbon emission reduction;
calculating a carbon emission saturation value of the target city according to the allowable value, and determining a moderate value of a relevant index of low carbon emission reduction;
obtaining subjective weight and objective weight, and calculating a satisfaction value of relevant indexes of low carbon emission reduction;
determining relevant thresholds and parameters according to the fitness value, the impermissible value and the satisfaction value.
The working principle and the beneficial effects of the technical scheme are as follows:
the index attribute unit of the technical scheme is used for acquiring relevant thresholds and parameters of the low-carbon emission reduction condition, and also comprises a large data center which is based on the preset, collects the preset urban carbon emission standard and calculates the allowable value of the relevant index of the low-carbon emission reduction; calculating a carbon emission saturation value of the target city according to the allowable value, and determining a moderate value of a relevant index of low carbon emission reduction; obtaining subjective weight and objective weight, and calculating a satisfaction value of related indexes of low carbon emission reduction; and determining related threshold values and parameters according to the fitness value, the impermissible value and the satisfaction value, and calculating the mixed weight of low carbon emission reduction through the subjective weight of an expert and the objective weight specified by documents or standards, so that the satisfaction of low carbon emission reduction is achieved, the personalized and targeted low carbon emission reduction target is designed, the conditions are met according to the place, and a better, more scientific and more reasonable low carbon emission reduction mode is achieved.
Example 10:
this technical solution provides an embodiment, wherein the optimization module includes:
an evaluation score unit: the system is used for receiving the evaluation result and generating a corresponding evaluation score based on a preset evaluation mechanism;
an analysis result unit: the evaluation score is analyzed and diagnosed based on a preset big data processing center to generate an analysis result;
learning data unit: the system is used for digitizing the analysis result, performing feature extraction and learning on the analysis result, and training corresponding learning data;
optimizing a data unit: for generating corresponding optimized data based on the learning data;
an optimization unit: and the evaluation index system is optimized through the optimization data.
The working principle and the beneficial effects of the technical scheme are as follows:
the optimization module comprises an evaluation score unit, an analysis result unit, a learning data unit, an optimization data unit and an optimization unit, wherein the evaluation score unit is used for receiving an evaluation result and generating a corresponding evaluation score based on a preset evaluation mechanism; the analysis result unit is used for carrying out analysis and diagnosis on the evaluation score based on a preset big data processing center to generate an analysis result; the learning data unit is used for digitizing the analysis result, performing characteristic extraction and learning on the analysis result and training corresponding learning data; the optimization data unit is used for generating corresponding optimization data based on the learning data; the optimization unit is used for optimizing the evaluation index system through the optimization data, and provides a flexible and self-adaptive evaluation optimization mode, so that the robustness of the evaluation system is improved, and the operation efficiency of evaluation is accelerated.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. The utility model provides an urban low carbon emission reduction evaluation system which characterized in that includes:
an acquisition module: the method comprises the steps of acquiring and collecting parameter indexes of a target city based on a preset DPSIR model; wherein the content of the first and second substances,
the parameter indexes at least include a driving force index, a pressure index, a response index, a state index and an influence index;
evaluation index system module: the method comprises the steps of selecting an evaluation index through a preset standard criterion and parameter index of low carbon emission reduction, and establishing an evaluation index system through the evaluation index;
an evaluation module: the evaluation index system is used for evaluating the parameter index based on the evaluation index system and generating an evaluation result;
an optimization module: and the system is used for carrying out diagnosis and analysis on the evaluation result, generating optimized data and optimizing an evaluation index system through the optimized data.
2. The system of claim 1, wherein the collection module comprises:
class classification index system unit: the system is used for collecting the carbon related indexes of a target city based on a preset DPSIR model, classifying the carbon related indexes of the target city and constructing an equal class classification index system;
carbon emission index unit: the system is used for analyzing and grading the classification index systems based on a preset fuzzy mathematical method, and determining the carbon emission index;
a parameter index unit: and the system is used for acquiring and collecting the parameter index of the target city through the carbon emission index.
3. The urban low carbon emission reduction assessment system according to claim 2, wherein the class classification index system unit comprises:
DPSIR model subunit: the system comprises a data acquisition unit, a data processing unit and a data processing unit, wherein the data acquisition unit is used for acquiring a driving force index, a pressure index, a response index, a state index and an influence index of urban carbon emission based on a preset DPSIR model; wherein the content of the first and second substances,
the driving force index comprises a carbon emission index of social and economic activities and industrial development;
the pressure index comprises a carbon emission index of resource energy consumption and environmental pollution emission;
the response indicator comprises a carbon emission reduction response indicator;
the state indexes comprise carbon emission indexes of change of the ecological system state and the environmental state;
the influence indexes comprise environmental change results and carbon emission indexes of social and economic influences;
contrast matrix subunit: the method is used for analyzing the relation among all indexes based on a preset analytic hierarchy process, and establishing a contrast matrix through the relation;
class classification index system subunit: and the system is used for classifying all indexes through the comparison matrix and constructing an equal class classification index system.
4. The urban low carbon emission reduction evaluation system according to claim 2, wherein the carbon emission index unit comprises:
carbon source discharge subunit: the method is used for analyzing indexes in a peer classification index system through a preset principal component analysis method and determining a carbon emission source;
a statistics result subunit: the system is used for clustering and counting the carbon emission sources through a preset fuzzy clustering method and a multivariate statistical method, and determining a statistical result;
class classification index system subunit: the method is used for carrying out hierarchical analysis on the statistical result based on a preset triangular fuzzy hierarchical analysis method and constructing an equal-class hierarchical index system;
carbon rejection indicator subunit: the system is used for determining the carbon emission index through the class grading index system.
5. The urban low carbon emission reduction assessment system according to claim 3, wherein the isoclass classification index system subunit is configured to classify all indexes through the comparison matrix, and construct an isoclass classification index system, further comprising:
establishing a corresponding variable measurement error model based on the comparison matrix;
performing parameter estimation through the variable measurement error model to determine an error parameter matrix;
calculating the error parameter matrix according to preset iteration times, determining an error iteration value, judging whether the error iteration value is greater than a preset classification error threshold value or not, and determining a judgment result;
when the judgment result is larger than or equal to a preset classification error threshold value, adding 1 to the number of the existing index types, classifying the corresponding indexes into a new type, and automatically calculating the next index;
when the judgment result is smaller than a preset classification error threshold value, classifying the corresponding index into the currently calculated index type, and automatically calculating the next index;
and when all the indexes are classified, generating a classification result, and constructing an equal class classification index system according to the classification result.
6. The system as claimed in claim 3, wherein the DPSIR model subunit collects a driving force index, a pressure index, a response index, a state index and an influence index of urban carbon emission based on a preset DPSIR model, and further comprises:
acquiring acquisition requirements of different indexes based on a preset DPSIR model;
compiling an automatic acquisition task based on the acquisition requirement; wherein the content of the first and second substances,
the automatic acquisition task comprises a task name, a task type, an acquisition group and an acquisition data item;
acquiring carbon related indexes of a target city through the automatic acquisition task, and recording acquisition task information; wherein the content of the first and second substances,
the collection task information at least comprises task execution starting and ending time, a collection period, execution priority and normal collection times.
7. The system of claim 1, wherein the evaluation index system module comprises:
primary evaluation index system unit: the system is used for carrying out frequency analysis on the parameter indexes through a preset low-carbon emission reduction standard criterion and establishing a primary evaluation index system;
a research and screening unit: the system is used for researching and screening the primary evaluation index system and calculating the index weight of each index in the primary evaluation index system;
a low-carbon emission reduction condition unit: the system is used for sequencing the index weights based on a preset fuzzy comprehensive evaluation system to determine the low-carbon emission reduction condition;
an index attribute unit: the method comprises the steps of obtaining relevant thresholds and parameters of the low-carbon emission reduction condition, and analyzing index attributes according to the relevant thresholds and parameters; wherein the content of the first and second substances,
the index attributes comprise a forward index attribute and a reverse index attribute;
evaluation index system unit: and the evaluation index system is constructed according to the index attribute and the primary evaluation index system.
8. The urban low carbon emission reduction assessment system according to claim 7, wherein the low carbon emission reduction situation unit comprises:
a weighting indicator subunit: the system is used for acquiring the index weights, weighting each index weight and determining a weighted index;
average indicator subunit: the weighting indexes are averaged to determine an average index;
the comprehensive evaluation value subunit: the method is used for evaluating the average index based on a preset fuzzy comprehensive evaluation system average to obtain a comprehensive evaluation value;
a low carbon emission reduction status subunit: and the method is used for sequencing the low-carbon emission of different areas according to the evaluation value and analyzing the low-carbon emission reduction condition.
9. The urban low carbon emission reduction assessment system according to claim 7, wherein the index attribute unit is configured to obtain relevant thresholds and parameters of low carbon emission reduction conditions, and further comprises:
acquiring a preset urban carbon emission standard based on a preset big data center, and calculating an allowable value of a relevant index of low carbon emission reduction;
calculating a carbon emission saturation value of the target city according to the allowable value, and determining a moderate value of a relevant index of low carbon emission reduction;
obtaining subjective weight and objective weight, and calculating a satisfaction value of related indexes of low carbon emission reduction;
determining relevant thresholds and parameters according to the fitness value, the impermissible value and the satisfaction value.
10. The system of claim 1, wherein the optimization module comprises:
an evaluation score unit: the system is used for receiving the evaluation result and generating a corresponding evaluation score based on a preset evaluation mechanism;
an analysis result unit: the evaluation score is analyzed and diagnosed based on a preset big data processing center to generate an analysis result;
learning data unit: the system is used for digitizing the analysis result, performing feature extraction and learning on the analysis result, and training corresponding learning data;
optimizing a data unit: for generating corresponding optimized data based on the learning data;
an optimization unit: and the system is used for optimizing the evaluation index system through the optimization data.
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