JP2021105807A5 - - Google Patents
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- JP2021105807A5 JP2021105807A5 JP2019236299A JP2019236299A JP2021105807A5 JP 2021105807 A5 JP2021105807 A5 JP 2021105807A5 JP 2019236299 A JP2019236299 A JP 2019236299A JP 2019236299 A JP2019236299 A JP 2019236299A JP 2021105807 A5 JP2021105807 A5 JP 2021105807A5
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- 238000004458 analytical method Methods 0.000 claims 12
- 238000000034 method Methods 0.000 claims 12
- 238000004422 calculation algorithm Methods 0.000 claims 4
- 238000004364 calculation method Methods 0.000 claims 3
Claims (14)
プロセッサ、前記プロセッサに接続されるメモリ、及び前記プロセッサに接続されるネットワークインタフェースを有する少なくとも一つの計算機を含み、
複数の特徴量を含むデータを前記推論部に入力することによって得られた推論結果を解釈するための解釈指標を算出する解釈指標算出部と、
前記解釈指標に基づいて、現在の前記業務システムの運用環境を解析し、前記解析の結果を出力する解析部と、を備え、
前記解釈指標は、前記推論部に入力された前記データに含まれる前記複数の特徴量の各々の前記推論結果に対する影響度を成分とする根拠ベクトルであることを特徴とする計算機システム。 A computer system that analyzes the operating environment of a business system that has an inference unit that makes inferences.
Includes a processor, memory connected to the processor, and at least one computer having a network interface connected to the processor.
An interpretation index calculation unit that calculates an interpretation index for interpreting the inference result obtained by inputting data including a plurality of features into the inference unit, and an interpretation index calculation unit.
It is equipped with an analysis unit that analyzes the current operating environment of the business system based on the interpretation index and outputs the result of the analysis.
The computer system is characterized in that the interpretation index is a basis vector whose component is the degree of influence of each of the plurality of feature quantities contained in the data input to the inference unit on the inference result.
前記解析部は、
前記根拠ベクトルを用いたクラスタリングを実行し、
前記クラスタリングの結果に基づいて、前記業務システムの運用環境の変化が発生したか否かを判定し、
前記クラスタリングの結果及び前記判定の結果を出力することを特徴とする計算機システム。 The computer system according to claim 1.
The analysis unit
Perform clustering using the basis vector,
Based on the result of the clustering, it is determined whether or not a change in the operating environment of the business system has occurred.
A computer system characterized by outputting the result of the clustering and the result of the determination.
前記解析部は、
前記クラスタリングの結果に基づいてクラスタ情報を生成し、
過去に生成された前記クラスタ情報と、新たに生成された前記クラスタ情報とを比較することによって、新規クラスタが出現したか否かを判定し、
前記新規クラスタが出現した場合、前記業務システムの運用環境の変化が発生したと判定することを特徴とする計算機システム。 The computer system according to claim 2.
The analysis unit
Cluster information is generated based on the result of the clustering, and
By comparing the cluster information generated in the past with the newly generated cluster information, it is determined whether or not a new cluster has appeared.
A computer system characterized in that when a new cluster appears, it is determined that a change in the operating environment of the business system has occurred.
前記解析部は、
前記新規クラスタに属する前記データの前記推論結果の精度を解析することによって、前記推論部の推論の精度が低下しているか否かを判定し、
前記推論部の推論の精度が低下していると判定された場合、前記推論部の推論の精度の低下を通知する情報を出力することを特徴とする計算機システム。 The computer system according to claim 3.
The analysis unit
By analyzing the accuracy of the inference result of the data belonging to the new cluster, it is determined whether or not the inference accuracy of the inference unit is lowered.
A computer system characterized by outputting information notifying that the inference accuracy of the inference unit is reduced when it is determined that the inference accuracy of the inference unit is low.
前記解析部は、ソート条件に基づいて、前記データをソートし、前記ソートの結果を出力することを特徴とする計算機システム。 The computer system according to claim 2.
The computer system is characterized in that the analysis unit sorts the data based on a sort condition and outputs the result of the sort.
前記ソート条件は、前記特徴量、前記根拠ベクトル、前記データの時系列、前記データが属するクラスタ、前記推論結果、及び前記推論結果の精度の少なくともいずれかであることを特徴とする計算機システム。 The computer system according to claim 5.
The sorting condition is at least one of the feature amount, the basis vector, the time series of the data, the cluster to which the data belongs, the inference result, and the accuracy of the inference result.
前記解釈指標算出部は、計算アルゴリズムに基づいて前記解釈指標を算出し、
前記解析部は、前記解析の結果に基づいて、前記計算アルゴリズムを更新することを特徴とする計算機システム。 The computer system according to claim 1.
The interpretation index calculation unit calculates the interpretation index based on the calculation algorithm.
The analysis unit is a computer system characterized in that the calculation algorithm is updated based on the result of the analysis.
前記計算機システムは、プロセッサ、前記プロセッサに接続されるメモリ、及び前記プロセッサに接続されるネットワークインタフェースを有する少なくとも一つの計算機を含み、
前記業務システムの運用環境の解析方法は、
前記少なくとも一つの計算機が、複数の特徴量を含むデータを前記推論部に入力することによって得られた推論結果を解釈するための解釈指標を算出する第１のステップと、
前記少なくとも一つの計算機が、前記解釈指標に基づいて、現在の前記業務システムの運用環境を解析し、前記解析の結果を出力する第２のステップと、含み、
前記解釈指標は、前記推論部に入力された前記データに含まれる前記複数の特徴量の各々の前記推論結果に対する影響度を成分とする根拠ベクトルであることを特徴とする業務システムの運用環境の解析方法。 It is an analysis method of the operating environment of a business system that has an inference unit that performs inference, which is executed by a computer system.
The computer system includes a processor, a memory connected to the processor, and at least one computer having a network interface connected to the processor.
The method of analyzing the operating environment of the business system is as follows.
A first step in which the at least one computer calculates an interpretation index for interpreting an inference result obtained by inputting data including a plurality of feature quantities into the inference unit.
The at least one computer analyzes the current operating environment of the business system based on the interpretation index, and includes a second step of outputting the result of the analysis.
The interpretation index is a basis vector whose component is the degree of influence of each of the plurality of feature quantities included in the data input to the inference unit on the inference result. analysis method.
前記第２のステップは、
前記少なくとも一つの計算機が、前記根拠ベクトルを用いたクラスタリングを実行する第３のステップと、
前記少なくとも一つの計算機が、前記クラスタリングの結果に基づいて、前記業務システムの運用環境の変化が発生したか否かを判定する第４のステップと、
前記少なくとも一つの計算機が、前記クラスタリングの結果及び前記判定の結果を出力する第５のステップと、を含むことを特徴とする業務システムの運用環境の解析方法。 The method for analyzing the operating environment of the business system according to claim 8.
The second step is
A third step in which the at least one computer performs clustering using the basis vector,
A fourth step in which the at least one computer determines whether or not a change in the operating environment of the business system has occurred based on the result of the clustering.
A method for analyzing an operating environment of a business system, wherein the at least one computer includes a fifth step of outputting the result of the clustering and the result of the determination.
前記第３のステップは、前記少なくとも一つの計算機が、前記クラスタリングの結果に基づいてクラスタ情報を生成するステップを含み、
前記第４のステップは、
前記少なくとも一つの計算機が、過去に生成された前記クラスタ情報と、新たに生成された前記クラスタ情報とを比較することによって、新規クラスタが出現したか否かを判定するステップと、
前記少なくとも一つの計算機が、前記新規クラスタが出現した場合、前記業務システムの運用環境の変化が発生したと判定するステップと、を含むことを特徴とする業務システムの運用環境の解析方法。 The method for analyzing the operating environment of the business system according to claim 9.
The third step includes a step in which the at least one computer generates cluster information based on the result of the clustering.
The fourth step is
A step in which the at least one computer determines whether or not a new cluster has appeared by comparing the previously generated cluster information with the newly generated cluster information.
A method for analyzing an operating environment of a business system, wherein the at least one computer includes a step of determining that a change in the operating environment of the business system has occurred when the new cluster appears.
前記第４のステップは、
前記少なくとも一つの計算機が、前記新規クラスタに属する前記データの前記推論結果の精度を解析することによって、前記推論部の推論の精度が低下しているか否かを判定するステップと、
前記推論部の推論の精度が低下していると判定された場合、前記少なくとも一つの計算機が、前記推論部の推論の精度の低下を通知する情報を出力するステップと、を含むことを特徴とする業務システムの運用環境の解析方法。 The method for analyzing the operating environment of the business system according to claim 10.
The fourth step is
A step of determining whether or not the inference accuracy of the inference unit is lowered by the at least one computer analyzing the accuracy of the inference result of the data belonging to the new cluster.
When it is determined that the inference accuracy of the inference unit is low, the at least one computer includes a step of outputting information notifying that the inference accuracy of the inference unit is low. How to analyze the operating environment of the business system to be used.
前記第２のステップは、
前記少なくとも一つの計算機が、ソート条件に基づいて、前記データをソートするステップと、
前記少なくとも一つの計算機が、前記ソートの結果を出力するステップと、を含むことを特徴とする業務システムの運用環境の解析方法。 The method for analyzing the operating environment of the business system according to claim 9.
The second step is
A step in which the at least one computer sorts the data based on the sorting conditions.
A method for analyzing an operating environment of a business system, wherein the at least one computer includes a step of outputting the result of the sort.
前記ソート条件は、前記特徴量、前記根拠ベクトル、前記データの時系列、前記データが属するクラスタ、前記推論結果、及び前記推論結果の精度の少なくともいずれかであることを特徴とする業務システムの運用環境の解析方法。 The method for analyzing the operating environment of the business system according to claim 12.
The operation of the business system characterized in that the sort condition is at least one of the feature amount, the basis vector, the time series of the data, the cluster to which the data belongs, the inference result, and the accuracy of the inference result. How to analyze the environment.
前記第１のステップは、前記少なくとも一つの計算機が、計算アルゴリズムに基づいて前記解釈指標を算出するステップを含み、
前記業務システムの運用環境の解析方法は、前記少なくとも一つの計算機が、前記解析の結果に基づいて、前記計算アルゴリズムを更新するステップを含むことを特徴とする業務システムの運用環境の解析方法。 The method for analyzing the operating environment of the business system according to claim 8.
The first step includes a step in which the at least one computer calculates the interpretation index based on a calculation algorithm.
The method for analyzing the operating environment of a business system is a method for analyzing the operating environment of a business system , wherein the at least one computer includes a step of updating the calculation algorithm based on the result of the analysis.
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| JP2015194791A (en) * | 2014-03-31 | 2015-11-05 | 日本電気株式会社 | Pos terminal equipment |
| JP6679266B2 (en) * | 2015-10-15 | 2020-04-15 | キヤノン株式会社 | Data analysis device, data analysis method and program |
| JP6685124B2 (en) * | 2015-12-22 | 2020-04-22 | 株式会社日立製作所 | Diagnostic device and diagnostic method |
| WO2018015988A1 (en) * | 2016-07-19 | 2018-01-25 | 株式会社オプティム | Person painting identification system, person painting identification method, and program |
| JP7032623B2 (en) * | 2017-10-31 | 2022-03-09 | 株式会社デンソー | Inference device, inference method and program |
| JP2021018466A (en) * | 2019-07-17 | 2021-02-15 | 株式会社ＰＫＳＨＡ Ｔｅｃｈｎｏｌｏｇｙ | Rule extracting apparatus, information processing apparatus, rule extracting method, and rule extracting program |
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