This paper describes the design and implementation of a hydraulic circuit design system using case-based reasoning (CBR) paradigm from AI community The domain of hydraulic circuit design and case-based reasoning are ...This paper describes the design and implementation of a hydraulic circuit design system using case-based reasoning (CBR) paradigm from AI community The domain of hydraulic circuit design and case-based reasoning are briefly reviewed Then a proposed methodology in compuer-aided circuit design and dynamic leaning with the use of CBR is described Finally an application example is selected to illustrate the ussfulness of applying CBR in hydraulic circuit design with leaming.展开更多
A computer-based pattern recognition systems has been developed for geological interpretation of Acoustic Sea-bed Profiling Records. Based on practical experience accumu- lated by specialists, the main pattern charact...A computer-based pattern recognition systems has been developed for geological interpretation of Acoustic Sea-bed Profiling Records. Based on practical experience accumu- lated by specialists, the main pattern characteristics of Acoustic Sea-bed Profiling Records (ASPRs) corresponding to typical geological categories of marine sediment layers in the area of the East China Sea have been expressed altogether in 9 aspects, and a dynamic reasoning expert system designed correspondingly. Starting from an initial premise Characteristic and makes the next step reasoning until the final conclusion (i.e. which geological category the sediment layer belongs to.) is derived, in the mean time, for quantitatively estimating the correctness of the final conclusions, the so-called certainty factor is calculated.展开更多
The interpretability of deep neural networks has aroused widespread concern in the academic and industrial fields.This paper proposes a new method named the dynamic reasoning and information bottleneck(DRIB)to improve...The interpretability of deep neural networks has aroused widespread concern in the academic and industrial fields.This paper proposes a new method named the dynamic reasoning and information bottleneck(DRIB)to improve human interpretability and understandability.In the method,a novel dynamic reasoning decision algorithmwas proposed to reduce multiply accumulate operations and improve the interpretability of the calculation.The information bottleneck was introduced to the DRIB model to verify the attribution correctness of the dynamic reasoning module.The DRIB reduces the burden approximately 50%by decreasing the amount of computation.In addition,DRIB keeps the correct rate at approximately 93%.The information bottleneck theory verifies the effectiveness of this method,and the credibility is approximately 85%.In addition,through visual verification of this method,the highlighted area can reach 50%of the predicted area,which can be explained more obviously.Some experiments prove that the dynamic reasoning decision algorithm and information bottleneck theory can be combined with each other.Otherwise,the method provides users with good interpretability and understandability,making deep neural networks trustworthy.展开更多
文摘This paper describes the design and implementation of a hydraulic circuit design system using case-based reasoning (CBR) paradigm from AI community The domain of hydraulic circuit design and case-based reasoning are briefly reviewed Then a proposed methodology in compuer-aided circuit design and dynamic leaning with the use of CBR is described Finally an application example is selected to illustrate the ussfulness of applying CBR in hydraulic circuit design with leaming.
基金the National 863 Plan Youth Foundation of China !(820-Q-09).
文摘A computer-based pattern recognition systems has been developed for geological interpretation of Acoustic Sea-bed Profiling Records. Based on practical experience accumu- lated by specialists, the main pattern characteristics of Acoustic Sea-bed Profiling Records (ASPRs) corresponding to typical geological categories of marine sediment layers in the area of the East China Sea have been expressed altogether in 9 aspects, and a dynamic reasoning expert system designed correspondingly. Starting from an initial premise Characteristic and makes the next step reasoning until the final conclusion (i.e. which geological category the sediment layer belongs to.) is derived, in the mean time, for quantitatively estimating the correctness of the final conclusions, the so-called certainty factor is calculated.
文摘The interpretability of deep neural networks has aroused widespread concern in the academic and industrial fields.This paper proposes a new method named the dynamic reasoning and information bottleneck(DRIB)to improve human interpretability and understandability.In the method,a novel dynamic reasoning decision algorithmwas proposed to reduce multiply accumulate operations and improve the interpretability of the calculation.The information bottleneck was introduced to the DRIB model to verify the attribution correctness of the dynamic reasoning module.The DRIB reduces the burden approximately 50%by decreasing the amount of computation.In addition,DRIB keeps the correct rate at approximately 93%.The information bottleneck theory verifies the effectiveness of this method,and the credibility is approximately 85%.In addition,through visual verification of this method,the highlighted area can reach 50%of the predicted area,which can be explained more obviously.Some experiments prove that the dynamic reasoning decision algorithm and information bottleneck theory can be combined with each other.Otherwise,the method provides users with good interpretability and understandability,making deep neural networks trustworthy.
