CN101474098A - Diagnoses and calling system of fish disease - Google Patents
Diagnoses and calling system of fish disease Download PDFInfo
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- CN101474098A CN101474098A CNA2008102275200A CN200810227520A CN101474098A CN 101474098 A CN101474098 A CN 101474098A CN A2008102275200 A CNA2008102275200 A CN A2008102275200A CN 200810227520 A CN200810227520 A CN 200810227520A CN 101474098 A CN101474098 A CN 101474098A
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Abstract
The invention discloses a fish disease diagnosis call system, which comprises a call information input device used for inputting attribute codes of pathological features of fish disease and a fish disease expert diagnosis system. The fish disease expert diagnosis system comprises a fish disease diagnosis database subsystem and a fish disease retrieval subsystem. The fish disease diagnosis subsystem stores the attribute codes of each item of pathological features of fish disease and fish disease case and preventive treatment information corresponding to every fish disease. The fish disease retrieval subsystem is used for retrieving the best match attribute code values of pathological features of fish disease from the fish disease diagnosis database subsystem according to the attribute codes of pathological features of fish disease input from the call information system and feedbacks the corresponding fish disease case and preventing treatment information. The invention increases the flexibility and functionality of the call system. A calling party can flexibly input each item of pathological information of fish disease to the call system by the encoded information input (such as digital) and obtains the corresponding feedback information from the call system. In particular, the system is suitable for the call information feedback of the system automatic feedback (that is, in the situation of without men on duty).
Description
Technical field
The present invention relates to agricultural system and management engineering technical field, particularly relate to a kind of diagnoses and calling system of fish disease.
Background technology
In recent years, the freshwater aquaculture industry of China is just with extraordinary speed development, output accounts for more than 70% of aquaculture total output, but when fresh-water fish-culture already develops rapidly, culture the generation of fish evil and popularly also be on the rise, national aquiculture disease kind was nearly 185 kinds in 2002, and the direct economic loss that causes reaches 14,100,000,000 yuan.According to preliminary survey, because the influence of disease, the survival rate of some regional Ctenopharyngodon idellus from the fry to the adult fish has only 10%～15%, 3～13 centimetres of fingerling survival rates of the pond Ctenopharyngodon idellus that has only 10%, more severe patient only is 5%, and this has caused bigger economic loss for the country and the family of breeding fish.How to make breeding production step into the road of sound development, become everybody questions of common interest.Therefore the research and extension of the diagnosis and treatment method of cultured freshwater fish disease is the task of top priority of freshwater aquaculture industry.
In order to reduce the loss that disease is brought, except the knowledge of popularizing fish disease diagnosis and control, research and develop various fish disease diagnosis specialist systems, assist to breed fish Producer diagnosis and treatment fish diseases early, just become the main exercise question of domestic and international each research institution.Main fish disease diagnosis Expert System Study has the Wang Chengzhi of Collects The American University in 1997 at present, Huang Shaotao, fish diseases diagnosis and treatment specialist system---" the fish doctor " that Ji Rongxing proposes; Daniel Zeldis, people such as Shawn Prescott have developed a test macro by the more different application of expert system technology in fish disease diagnosis, integrated fuzzy theory, rule-based and statistical method, and common application is in fish disease diagnosis; On application network technological development fish diseases remote diagnosis Study on Expert System, Daoliang Li, Zetian Fu, Yanqing Duan developed the fish disease diagnosis specialist system based on Web in 2002.Along with the improving constantly of the penetration of computer use in this year, the fish diseases specialist system promoted the use of very great development.But the popularization of specialist system must be by means of infrastructure such as the Internet and computers, and also have the popularity of a lot of regional computers relatively low, even in the place that the basis for IT application facility is arranged, study and use specialist system also need certain basis and time, so the fish diseases specialist system is popularized very big difficulty in addition in China.Calling system based on communication network has solved the problems referred to above well, but still there is certain deficiency in common calling system, just must be manually on duty such as solving more complicated a little fish diseases problems, if relied on feed back automatically fully in 24 hours of system, the information mode that can provide is all preset, but the choice of MPTY is less, can't solve comparatively complicated fish diseases problem.
Summary of the invention
The problem that the embodiment of the invention will solve provides a kind of diagnoses and calling system of fish disease, provides the remote information service to be embodied as the raiser, helps its diagnosis fish diseases, and corresponding prevention and treatment method is provided.
For achieving the above object, the technical scheme of the embodiment of the invention provides a kind of diagnoses and calling system of fish disease, described system comprises call information input equipment and the fish diseases expert diagnostic system that is used to import fish diseases pathological characters attribute codes, wherein, described fish diseases expert diagnostic system comprises: the fish disease diagnosis database subsystem, and store the fish diseases case of every pathological characters attribute codes of every kind of fish diseases and every kind of fish diseases correspondence and preventing and treating information; The fish diseases retrieval subsystem is used for retrieving the fish diseases pathological characters attribute codes value of mating most according to the fish diseases pathological characters attribute codes of importing from call information input equipment from the fish disease diagnosis database subsystem, and feeds back corresponding fish diseases case and prevent and treat information.
Wherein, described fish diseases pathological characters attribute codes comprises: whether expression exists the state parameter of this kind pathological phenomenon state.
Wherein, described fish diseases case attribute codes also comprises: the weights of representing this kind pathological phenomenon proportion in whole pathological phenomenon.
Wherein, described fish diseases retrieval subsystem is being stored the index information of fish diseases case database, and described index information adopts the C-means clustering algorithm, represents a kind of disease with a polymerization site, kind number by disease is divided into several polymerization site, carries out the fish diseases information index by polymerization site.
Wherein, the dynamic clustering of described C-means clustering algorithm adopts genetic algorithm to realize.
Wherein, described call information input equipment is mobile phone or landline telephone or other communication terminals.
Wherein, described fish diseases pathological characters attribute codes is by the button input of described mobile phone or landline telephone or other communication terminals.
Compared with prior art, technical scheme of the present invention has following advantage:
The embodiment of the invention has improved the motility of calling system and functional, MPTY can be imported every pathological information of fish diseases neatly by the information input (as numeral) of encode to calling system, and from calling system, obtaining corresponding feedback information, the system that is specially adapted to feeds back the call information feedback of (promptly not having under the artificial situation on duty) automatically.Therefore, the embodiment of the invention can be replenished as the effective of specialist system who with the computer is media by landline telephone and mobile phone, and the fish disease prevention and cure knowledge dissemination is arrived the relatively low area of the penetration of computer use
Description of drawings
Fig. 1 is a kind of diagnoses and calling system of fish disease structural representation of the embodiment of the invention;
Fig. 2 is a kind of fish diseases detection of the embodiment of the invention and the flow chart of diagnostic procedure;
Fig. 3 is a kind of Fish Disease Diagnose Reasoning system structure sketch map of the embodiment of the invention;
Fig. 4 is the flow chart of a kind of Fish Disease Diagnose Reasoning process of the embodiment of the invention.
The specific embodiment
Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail.Following examples are used to illustrate the present invention, but are not used for limiting the scope of the invention.
A kind of diagnoses and calling system of fish disease structure of the embodiment of the invention as shown in Figure 1, the diagnoses and calling system of fish disease of present embodiment comprises call information input equipment and the fish diseases expert diagnostic system that is used to import fish diseases pathological characters attribute codes, the fish diseases expert diagnostic system comprises the fish disease diagnosis database subset fish diseases retrieval subsystem of unifying, the fish disease diagnosis database subsystem is being stored the fish diseases case of every pathological characters attribute codes of every kind of fish diseases and every kind of fish diseases correspondence and is being prevented and treated information, described fish diseases retrieval subsystem is used for retrieving the fish diseases pathological characters attribute codes value of mating most according to the fish diseases pathological characters attribute codes of importing from call information input equipment from the fish disease diagnosis database subsystem, and feeds back corresponding fish diseases case and prevent and treat information.Also store fish diseases case database index information in the fish diseases retrieval subsystem, so that the user is during from call information input equipment input index information, retrieval subsystem is searched by index information from the fish disease diagnosis database subsystem.
Diagnoses and calling system of fish disease of the present invention to set up process as follows:
One, fish disease diagnosis
Fish disease diagnosis is exactly by various ways and means, the animation of observation and supervision fish, and according to known symptom, find out the diagnosed object fish and may have the immediate cause that maybe disease will take place and cause these diseases, to guarantee that the diagnosed object fish is in certain living environment and growth healthily in season.According to the purpose of fish disease diagnosis and the basic task that will finish, fish disease diagnosis has the implication of two aspects, and the first will be found out the reason that causes fish that disease takes place.It two is to make corresponding control strategy, method or suggestion according to different diseases.
A kind of fish diseases detection of the embodiment of the invention and diagnostic procedure are as shown in Figure 2.Mainly comprise following several respects job content in the fish disease diagnosis system:
1, adopts various detection meanss, people's suitable observed patterns such as sense organ,, detect the symptom of fish and the water quality condition of life thereof in the proper site of fish.
2, detected symptom, water quality information are carried out necessary processing, conversion, statistics and arrangement, therefrom extract the characteristic attribute of the features such as symptom relevant as fish disease diagnosis with fish diseases;
3, according to symptom and other diagnostic message that sick fish showed, adopt logic, that number is of science, artificial experience analysis or other method, the symptom of sick fish is discerned and analytical judgment, found out abnormal conditions and the disease of fish, and these abnormal conditions and disease are made a definite diagnosis.
4, in that abnormal conditions and disease are carried out on the basis of systematic analysis, adopt suitable decision-making formation method, fish diseases is prevented and treated decision-making and handled suggestion.
A common fish disease diagnosis system should comprise three be mutually related work process and functions, and they are respectively: fish diseases detection, fish diseases separation and identification and fish diseases are handled.It is to judge and whether definite fish disease has taken place that according to monitoring information it comprises field investigation, visual inspection, microscopy etc. that fish diseases detects; It then is the separating and identification process of fish diseases information such as time that the fish diseases that has taken place is taked to determine its kind, part taken place and disease occurs that fish diseases is separated with identification; It is exactly result according to fish diseases detection, separation and identification that fish diseases is handled, in conjunction with the knowledge of each side or rule etc., the strategy that proposes the fish diseases processing method and deal with problems.Three processes that fish diseases detects with diagnosis are interconnected with one another, often the latter's work be exactly with the former result as condition and basis, mutual group becomes fish diseases to detect a complete procedure with diagnosis.
Two, the case representation of fish diseases reasoning and collection
Case representation has the implication of two aspects, i.e. content and structure.It is meant that the mode of handling with modelling reflects the data and the relation thereof of case in computer-internal, so that realize the operation to case.The method for expressing of case is reflecting that not only can case be converted into the form of case easily, but also affects the efficient and the solving precision of reasoning by cases.
Case is description and the expression to an incident or problem, and the content of case representation has comprised and these incidents or the relevant various different information of problem, and case generally includes three key components: problem description, problem solving and case result.
At last, the case representation classification editor who obtains, typing case storehouse is inquired about and is called for call center system.
A kind of Fish Disease Diagnose Reasoning system structure of the embodiment of the invention as shown in Figure 3, a kind of Fish Disease Diagnose Reasoning process as shown in Figure 4.In the Fish Disease Diagnose Reasoning process, feature and content according to fish disease diagnosis, with the representation of characteristic vector as case, in order to narrate conveniently, we are example with the visual inspection process, omitted in the concrete case with the little disease phenomenon of reasoning by cases relation with prevent and treat content such as method, only pay close attention to the property attribute of the case relevant with fish diseases.
With the Cyprinus carpio is example, shows as unusual symptoms such as muscle, body surface, abdominal part, scale, head, fin, gill portion, intestinal when disease takes place.Therefore, when this disease fish was diagnosed, we set up its disease case with above-mentioned these 8 parameters as feature.What enumerate in table 1 is the Cyprinus carpio of setting up according to these features 5 cases when disease takes place, and each case is represented its different characteristics combination that is shown under morbid state.Do not consider the influence of feature weight to case in these cases, the role and influence of promptly supposing each case are all equal.
Table 1
| Numbering | Disease | Muscle | Body surface | Abdominal part | Scale | Head | Fin | Gill portion | Intestinal |
| Case1 | White head and mouth fish disease | 000 | A01 | 000 | 000 | B04 | 000 | 000 | 000 |
| Case2 | The enteritis disease | 000 | 000 | D01 | 000 | 000 | 000 | 000 | H03 |
| Case3 | Erythroderma | 000 | A04 | 000 | E01 | 000 | F01 | C03 | 000 |
| Case4 | Gill rot | 000 | 000 | 000 | 000 | B01 | 000 | C01 | 000 |
| Case5 | The scabies disease | 000 | A07 | 000 | 000 | 000 | F02 | 000 | 000 |
If as a row vector, then the case set of being made up of above-mentioned 5 cases can be by matrix notation each case:
In actual applications, different characteristic all exists certain difference to the role and influence of case, is the degree difference that this difference shows under different situations.The listed case of enumerating in the his-and-hers watches 1, if consider 8 difference that feature is used the influence and the work of case, give different weights to them after, can obtain a new case set, as shown in table 2.
Table 2
| Numbering | Muscle | Body surface | Abdominal part | Scale | Head | Fin | Gill portion | Intestinal | |
| Case1 | White head and mouth fish disease | 000 | A01 | 000 | 000 | B04 | 000 | 000 | 000 |
| Weights | 0 | 0.5 | 0 | 0 | 0.5 | 0 | 0 | 0 | |
| Case2 | The enteritis disease | 000 | 000 | D01 | 000 | 000 | 000 | 000 | H03 |
| Weights | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.5 | |
| Case3 | Erythroderma | 000 | A04 | 000 | E01 | 000 | F01 | C03 | 000 |
| Weights | 0 | 0.25 | 0 | 0.25 | 0 | 0 | 0.25 | 0 | |
| Case4 | Gill rot | 000 | 000 | 000 | 000 | B01 | 000 | C01 | 000 |
| Weights | 0 | 0 | 0 | 0 | 0.5 | 0 | 0.5 | 0 | |
| Case5 | The scabies disease | 000 | A07 | 000 | 000 | 000 | F02 | 000 | 000 |
| Weights | 0 | 0.5 | 0 | 0 | 0 | 0.5 | 0 | 0 |
Because the weight of feature and feature all may change in different cases, as above present head of the symptom of gill rot and weight table and gill portion in the example, and the symptom of enteritis disease and weight show abdominal part and intestinal, therefore it is a non-isomorphism case set, and we adopt the maximum feature set of case set to solve non-isomorphism problem for this reason.
As follows according to the incompatible case characteristic matrix F of organizing of maximum feature set:
Wherein, m is the feature number in the maximum characteristic set, promptly maximum characteristic number, and n is the number of case among the case set C.
In eigenmatrix F, each row is represented a case, and each row is represented the eigenvalue of a case characteristic in different cases, to each the element f in the matrix
I, j(we do following regulation for 1≤i≤n, the value of 1≤j≤m):
When feature j is feature among the case i, the value of its representation feature j in case i, otherwise, no practical significance, available suitable numerical value is arbitrarily filled the position of this element in matrix.
Similarly, we also become a matrix form to the weight of each feature in the case according to above-mentioned similar manner tissue, and claim that this matrix is the feature weight matrix.
Wherein, R is the feature weight matrix, and m is the feature number in the maximum characteristic set, and n is the number of case among the case set C.
In feature weight matrix R, each row is represented the feature weights of a case characteristic in different cases, to each the element r among the matrix R
I, j(1≤i≤n, the value of 1≤j≤m), wherein:
When feature j is feature among the case i, r
I, jThe weights of representation feature j in case i, otherwise, r
I, j=0.
On the basis of above-mentioned definition, case set C can be expressed as the product of the transposed matrix of the eigenmatrix of this case set and feature weight matrix:
C＝F·R
T
For example, utilize matrix can the case set by the fish diseases shown in the table 4.2 be expressed as:
Three, the retrieval of fish diseases case
Case retrieval be from case library, find and search out with current problem approximate and finding the solution of current problem had help or the case of directive significance in attribute character, up to finding a best coupling.It generally includes initial matching, search and selection.The target of initial matching is to return a series of cases, can be consistent with new case fully, and selection is meant to choose in these cases mates case preferably.The retrieving of case is divided into two steps usually to carry out, i.e. case index and case coupling.The case index is exactly according to certain index strategy, and elder generation's Preliminary screening from numerous cases goes out the casebook to current problem possibility or potentially useful, to dwindle range of search, improves seek rate; The case coupling is exactly to find out the case the most similar to current problem according to certain method for measuring similarity from the casebook that obtains through primary election.
All cases are divided into two-layer: bottom is all cases; The upper strata is a typical case, and each typical case has all been represented one or several and its very similar case, and the modification rule between typical case is most important, and domain expert's guidance should be arranged.The modification rule that obtains, most important for the measurement of semantic difference between similar cases, semanteme can be described by the keyword of index thesaurus definition, and the keyword of index thesaurus can be used for the description of case function and semantic net node equally.Use revising rule also needs the case evaluation, and promptly the evaluation of the answer that subsystem is provided because modification once can getable result be false, also will further be revised.Sometimes, problem can't be complementary with the former piece of some rules, and the former piece of several rules of problem need being videoed respectively this moment comprehensively becomes the deduction result of several rules the answer of whole problem at last.
1, case index
The index of case library (indexing) mechanism is a major issue of being paid close attention to, and its target provides a kind of search mechanisms of case library, makes can find out case or the casebook that suits the requirements fast in retrieval in the future.For the case retrieval, it is necessary setting up good case index.Good index can help fast, finds required case exactly.Index can be the surface characteristic of case or derive characteristic that surface characteristic can directly draw, and derives characteristic and then must just can obtain by certain reasoning from the description of case.Surface characteristic and derive characteristic and reflected our awareness to knowledge.Surface characteristic may make search too blindly in the case retrieval, and the derivation characteristic is the reaction to the deep intension of problem, the hunting zone is reduced, and tend to increase the analogy possibility of success.No matter be which kind of characteristic, the most important thing is that index should be the set of those keywords relevant naturally with reasoning or the process of dealing with problems, these keywords can make a distinction this case with other case.Index should be concrete, and is clearly, easy to identify.The index of case can have a plurality of, is respectively applied for different purposes, searching algorithm and should be able to uses the case index to find out suitable case under the prerequisite of time-constrain satisfying.This means that case should be indexed, make that in office what is the need for of case can be found when wanting.At this, the traditional information retrieval and the index technology of Database Systems can have good use for reference of planning.But the principle of setting up the case index is different with the index notion of conventional information retrieval and Database Systems.In traditional index notion, an important guiding theory is to keep the storage organization balance.
We use for reference the notion of cluster the present invention, adopt C-means clustering algorithm, represent a kind of disease with a polymerization site, are divided into several polymerization site by the kind number of disease, carry out index by polymerization site.
C mean cluster model is:
If object function
Wherein: cluster centre
(i＝1，2，...，r＝1，2，...P)，
m
rBe sample (record) number that belongs to the r class;
Expression sample X
iBelong to the r class;
N is sample (record) number; P is cluster centre number (2≤P≤N-1).
We find the solution the dynamic clustering problem with genetic algorithm.
The chromosomal structure of step 1
With X=(X
1, X
2..., X
N) the expression chromosome structure, X is 1 * N dimension row vector, X
kBe the gene of k position, then chromosome x
k∈ 1,2 ..., N} uses natural number coding, dynamically determines clusters number by chromosome.
The relevant parameter of genetic algorithm is set, max_gen: maximum iteration time; N: group size; Length: chromosome length; Pc: crossover probability; Pm: variation probability; P: initial cluster center; α: the parameter in the adaptive value function;
Step 2: colony's initialization
for?i＝1?to?N?do
for?j＝1?to?length?do
The gene of chromosome x i=random (0, P);
endfor
endfor
Step 3: calculate the adaptive value function
for?i＝1?to?N?do
Calculate the object function Ji of chromosome x i;
endfor
Target function value Ji according to chromosome x i sorts;
for?i＝1?to?N?do
Calculate the ideal adaptation degree
endfor
for?j＝1?to?N?do
Calculate the accumulation outline
endtor
Step 4: carry out selection operation
Step 5: carry out interlace operation
Step 6: carry out mutation operation
Step 7: elite's retention strategy
if(Minimumof?NewGeneration<Minimum?of?OldGeneration)then
Replace the poorest individuality in the filial generation with individuality best in the parent;
endfor
Step 8: dynamically change clusters number
If (the best individuality in the colony is in the interior not change of M generation) then
P=Popt+n, and change step 2;
else
Continue operation;
endif
Step 9: end condition check
if(gen<max_gen)then
Make gen=gen+1, and change step 3 over to;
else
Stop to calculate the output result
endif
2, rule-based and case searching algorithm
Rule-based as follows with searching algorithm case:
(1) defeated people's new case is according to the relevant regular rule description that generates new case of index generation;
(2) if similarity degree of judgment rule coding RULE_CODE identical, is then directly located case.If incomplete same, whether the similar value of analytic attribute is in threshold range; If in threshold value, then retrieve corresponding casebook; If not in threshold value, then mate, and then retrieve corresponding case according to the similarity of case.If the case that retrieves is unreasonable or can not retrieve case, change (4);
(3) in the process of retrieving, preserve all critical learning and the hobby of relevant case study process, be deposited into the heuristic knowledge storehouse.
(4) selected case system referent (object is through ordering) is according to the measuring similarity under the most adjoining improved method calculating object;
(5) whether also relate to other objects, if then get next object that the case system relates to; Otherwise change 5;
(6) calculate the total similarity of case system;
(7) case that similarity is the highest is exactly the result;
(8) whether this case user or expert are satisfied with.
If satisfied, then classify such case as the candidate casebook, finish reasoning.
Four, fish diseases reasoning case is embedded call center's module
These most crucial work of fish diseases reasoning are finished in first three step in fact, and this step only needs the module of front is embedded call center system, as the data base on backstage.And required index and keyword can directly be selected by user key-press in fish diseases case retrieving, or passes through user's voice, manual typing keyword by the seat personnel.In case retrieve correspondingly to example, the user can continue the instrument voice suggestion, and button selects to navigate to the method for preventing and treating (when design fish disease diagnosis process, with the method for the preventing and treating record of every kind of fish diseases as background data base) of this case.Utilize call center's strong functions, the platform of tripartite talks also can be provided to the user, get final product the designated time, carry out telephone counseling to relevant expert.
The above only is a preferred implementation of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the technology of the present invention principle; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (7)
1, a kind of diagnoses and calling system of fish disease is characterized in that, described system comprises call information input equipment and the fish diseases expert diagnostic system that is used to import fish diseases pathological characters attribute codes, and wherein, described fish diseases expert diagnostic system comprises:
The fish disease diagnosis database subsystem is being stored the fish diseases case of every pathological characters attribute codes of every kind of fish diseases and every kind of fish diseases correspondence and is being prevented and treated information;
The fish diseases retrieval subsystem is used for retrieving the fish diseases pathological characters attribute codes value of mating most according to the fish diseases pathological characters attribute codes of importing from call information input equipment from the fish disease diagnosis database subsystem, and feeds back corresponding fish diseases case and prevent and treat information.
2, diagnoses and calling system of fish disease as claimed in claim 1 is characterized in that, described fish diseases pathological characters attribute codes comprises: whether expression exists the state parameter of this kind pathological phenomenon state.
3, diagnoses and calling system of fish disease as claimed in claim 2 is characterized in that, described fish diseases case attribute codes also comprises: the weights of representing this kind pathological phenomenon proportion in whole pathological phenomenon.
4, diagnoses and calling system of fish disease as claimed in claim 3, it is characterized in that, described fish diseases retrieval subsystem is being stored the index information of fish diseases case database, described index information adopts the C-means clustering algorithm, represent a kind of disease with a polymerization site, kind number by disease is divided into several polymerization site, carries out the fish diseases information index by polymerization site.
5, diagnoses and calling system of fish disease as claimed in claim 4 is characterized in that, the dynamic clustering of described C-means clustering algorithm adopts genetic algorithm to realize.
As each described diagnoses and calling system of fish disease of claim 1 to 5, it is characterized in that 6, described call information input equipment is mobile phone or landline telephone or other communication terminals.
7, diagnoses and calling system of fish disease as claimed in claim 6 is characterized in that, described fish diseases pathological characters attribute codes is by the button input of described mobile phone or landline telephone or other communication terminals.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101877035A (en) * | 2010-04-22 | 2010-11-03 | 无锡市优特科科技有限公司 | Electrocardiogram analyzing system based on gold standard database |
| CN102124964B (en) * | 2010-01-15 | 2013-01-02 | 浙江海洋学院 | Intelligent management system for mariculture |
| CN104866979A (en) * | 2015-06-08 | 2015-08-26 | 苏芮 | Traditional Chinese medicine case data processing method and system of emergent acute infectious disease |
| CN117611380A (en) * | 2024-01-24 | 2024-02-27 | 中国水产科学研究院黄海水产研究所 | Fish disease early warning method and system |
-
2008
- 2008-11-27 CN CNA2008102275200A patent/CN101474098A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102124964B (en) * | 2010-01-15 | 2013-01-02 | 浙江海洋学院 | Intelligent management system for mariculture |
| CN101877035A (en) * | 2010-04-22 | 2010-11-03 | 无锡市优特科科技有限公司 | Electrocardiogram analyzing system based on gold standard database |
| CN101877035B (en) * | 2010-04-22 | 2015-09-09 | 无锡市优特科科技有限公司 | Based on the electrocardiograph system of goldstandard database |
| CN104866979A (en) * | 2015-06-08 | 2015-08-26 | 苏芮 | Traditional Chinese medicine case data processing method and system of emergent acute infectious disease |
| CN104866979B (en) * | 2015-06-08 | 2018-10-23 | 苏芮 | A kind of Chinese medicine case data processing method and system of burst acute infectious disease |
| CN117611380A (en) * | 2024-01-24 | 2024-02-27 | 中国水产科学研究院黄海水产研究所 | Fish disease early warning method and system |
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