We consider various tasks of recognizing properties of DRSs(Decision Rule Systems)in this paper.As solution algorithms,DDTs(Deterministic Decision Trees)and NDTs(Nondeterministic Decision Trees)are used.An NDT can be ...We consider various tasks of recognizing properties of DRSs(Decision Rule Systems)in this paper.As solution algorithms,DDTs(Deterministic Decision Trees)and NDTs(Nondeterministic Decision Trees)are used.An NDT can be considered as a representation of a DRS that satisfies the conditions of the considered task and covers all potential inputs.It has been shown that the minimum depth of a DDT solving the task does not exceed the square of the minimum depth of an NDT.The growth of the minimum number of nodes in DDTs and NDTs can be exponential with the size of the original DRSs.There-fore,in the general case,it is better to simulate the behavior of the DT(Deci-sion Tree)on the given tuple of feature values rather than building the entire tree.We propose a greedy algorithm for such modeling and study its efficiency for a class of tasks of recognizing properties of DRSs.The obtained results may be of interest for data analysis in which both DRSs and DTs are intensively studied.In particular,these results make one think about the possibilities of transforming DRSs into DTs.展开更多
The research aimed to construct an intelligent review system for construction projects based on Building Information Modeling(BIM)and rule engines.By establishing a BIM data standard system and utilizing Structured Na...The research aimed to construct an intelligent review system for construction projects based on Building Information Modeling(BIM)and rule engines.By establishing a BIM data standard system and utilizing Structured Naming Language(SNL)to formalize review rules,combined with model visualization and scene recognition technology,a cloud native platform with automated review capabilities has been developed.The pilot application shows that the system can effectively improve the efficiency and accuracy of planning and construction drawing review,providing a feasible technical solution for digital engineering review.展开更多
The mathematical topological rule was proposed to plot the predominance area diagram.Based on the phase rules,the components of In-S-O system were analyzed and the coexisting points of three condensed phases were dete...The mathematical topological rule was proposed to plot the predominance area diagram.Based on the phase rules,the components of In-S-O system were analyzed and the coexisting points of three condensed phases were determined.Combined with the topological rules and thermody namic calculation,four relation diagrams between the coexisting points of three condensed phases,which were denoted as α,β stable plane-topological diagram and unstable plane-topological diagram,were plotted for the In-S-O system.The results show that α stable plane topological diagram is in accordance with the predominance area diagram of In-S-O system plotted by traditional methods,which indicates that the new method is feasible to plot the predominance area diagram of In-S-O system.Meanwhile,β unstable plane-topological diagram can be used to elucidate the indium production with the bath smelting process.展开更多
Association rules are useful for determining correlations between items. Applying association rules to intrusion detection system (IDS) can improve the detection rate, but false positive rate is also increased. Weight...Association rules are useful for determining correlations between items. Applying association rules to intrusion detection system (IDS) can improve the detection rate, but false positive rate is also increased. Weighted association rules are used in this paper to mine intrustion models, which can increase the detection rate and decrease the false positive rate by some extent. Based on this, the structure of host-based IDS using weighted association rules is proposed.展开更多
Expert systems (ESs) are being increasingly applied to the fault diagnosis of engines. Based on the idea of ES template (EST), an object-oriented rule-type EST is emphatically studied on such aspects as the object-ori...Expert systems (ESs) are being increasingly applied to the fault diagnosis of engines. Based on the idea of ES template (EST), an object-oriented rule-type EST is emphatically studied on such aspects as the object-oriented knowledge representation, the heuristic inference engine with an improved depth-first search (DFS) and the graphical user interface. A diagnositic ES instance for debris on magnetic chip detectors (MCDs) is then created with the EST. The spot running shows that the rule-type EST enhances the abilities of knowledge representation and heuristic inference, and breaks a new way for the rapid construction and implementation of ES.展开更多
By the analysis of CORBA technology, distributed technology, multi agent, fuzzy cluster, OA system, expert system and decision support technology, a distributed OA expert system model based on fuzzy rules (DOAES) is ...By the analysis of CORBA technology, distributed technology, multi agent, fuzzy cluster, OA system, expert system and decision support technology, a distributed OA expert system model based on fuzzy rules (DOAES) is proposed. In DOAES, the knowledge and experience of decision makers are processed and transferred into the knowledge base. So the system has the adaptive ability and re study function and the decision results are more scientific and more objective. The DOAES is successfully applied in the management system of invest promotion.展开更多
Real-time and accurate fault detection is essential to enhance the aircraft navigation system’s reliability and safety. The existent detection methods based on analytical model draws back at simultaneously detecting ...Real-time and accurate fault detection is essential to enhance the aircraft navigation system’s reliability and safety. The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults. On account of this reason, we propose an online detection solution based on non-analytical model. In this article, the navigation system fault detection model is established based on belief rule base （BRB）, where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output. To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update, a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization （EM） algorithm. Furthermore, the proposed method is verified by navigation experiment. Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model. The output of the detection model can track the fault state very well, and the faults can be diagnosed in real time and accurately. In addition, the detection ability, especially in the probability of false detection, is superior to offline optimization method, and thus the system reliability has great improvement.展开更多
For real-time and distributed features of multi-robot system,the strategy of combining the improved artificial potential field method and the rules based on priority is proposed to study the collision avoidance planni...For real-time and distributed features of multi-robot system,the strategy of combining the improved artificial potential field method and the rules based on priority is proposed to study the collision avoidance planning in multi-robot systems. The improved artificial potential field based on simulated annealing algorithm satisfactorily overcomes the drawbacks of traditional artificial potential field method,so that robots can find a local collision-free path in the complex environment. According to the movement vector trail of robots,collisions between robots can be detected,thereby the collision avoidance rules can be obtained. Coordination between robots by the priority based rules improves the real-time property of multi-robot system. The combination of these two methods can help a robot to find a collision-free path from a starting point to the goal quickly in an environment with many obstacles. The feasibility of the proposed method is validated in the VC-based simulated environment.展开更多
Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence w...Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence were redefined. The algorithm can mine the association rules with decision attributes directly without processing missing values. Using the incomplete dataset Mushroom from UCI machine learning repository, the new algorithm was compared with the classical association rules mining algorithm based on Apriori from the number of rules extracted, testing accuracy and execution time. The experiment results show that the new algorithm has advantages of short execution time and high accuracy.展开更多
In new environments of trading, customer's trust is vital for the extended progress and development of electronic commerce. This paper proposes that in addition to known factors of electronic commerce B2C websites...In new environments of trading, customer's trust is vital for the extended progress and development of electronic commerce. This paper proposes that in addition to known factors of electronic commerce B2C websites such a design of websites, security of websites and familiarity of website influence customers trust in online transactions. This paper presents an application of expert system on trust in electronic commerce. Based on experts’ judgment, a frame of work was proposed. The proposed model applies ANFIS and Mamdani inference fuzzy system to get the desired results and then results of two methods were compared. Two questionnaires were used in this study. The first questionnaire was developed for e-commerce experts, and the second one was designed for the customers of electronic websites. Based on AHP method, Expert Choice software was used to determine the priority of factors in the first questionnaire, and MATLAB and Excel were used for developing the fuzzy rules. Finally, the fuzzy logical kit was used to analyze the generated factors in the model. Our study findings show that trust in EC transactions is strongly mediated by perceived security.展开更多
A new approach to knowledge acquisition in incomplete information system with fuzzy decisions is proposed. In such incomplete information system, the universe of discourse is classified by the maximal tolerance classe...A new approach to knowledge acquisition in incomplete information system with fuzzy decisions is proposed. In such incomplete information system, the universe of discourse is classified by the maximal tolerance classes, and fuzzy approximations are defined based on them. Three types of relative reducts of maximal tolerance classes are then proposed, and three types of fuzzy decision rules based on the proposed attribute description are defined. The judgment theorems and approximation discernibility functions with respect to them are presented to compute the relative reduct by using Boolean reasoning techniques, from which we can derive optimal fuzzy decision rules from the systems. At last, three types of relative reducts of the system and their computing methods are given.展开更多
Wind is one kind of clean and free renewable energy sources. Wind speed plays a pivotal role in the wind power output. However, due to the random and unstable nature of the wind, accurate prediction of wind speed is a...Wind is one kind of clean and free renewable energy sources. Wind speed plays a pivotal role in the wind power output. However, due to the random and unstable nature of the wind, accurate prediction of wind speed is a particularly challenging task. This paper presents a novel neural fuzzy method for the hourly wind speed prediction. Firstly, a neural structure is proposed for the functional-type single-input-rule-modules(FSIRMs) connected fuzzy inference system(FIS) to combine the merits of both the FSIRMs connected FIS and the neural network. Then, in order to achieve both the smallest training errors and the smallest parameters, a least square method based parameter learning algorithm is presented for the proposed FSIRMs connected neural fuzzy system(FSIRMNFS). Further,the proposed FSIRMNFS and its parameter learning algorithm are applied to the hourly wind speed prediction. Experiments and comparisons are also made to show the effectiveness and advantages of the proposed approach. Experimental results verified that our study has presented an effective approach for the hourly wind speed prediction. The proposed approach can also be used for the prediction of wind direction, wind power and some other prediction applications in the research field of renewable energy.展开更多
While the scattering phase for several one-dimensional potentials can be exactly derived, less is known in multi-dimensional quantum systems. This work provides a method to extend the one-dimensional phase knowledge t...While the scattering phase for several one-dimensional potentials can be exactly derived, less is known in multi-dimensional quantum systems. This work provides a method to extend the one-dimensional phase knowledge to multi-dimensional quantization rules. The extension is illustrated in the example of Bogomolny＇s transfer operator method applied in two quantum wells bounded by step potentials of different heights. This generalized semiclassical method accurately determines the energy spectrum of the systems, which indicates the substantial role of the proposed phase correction. Theoretically, the result can be extended to other semiclassical methods, such as Gutzwiller trace formula, dynamical zeta functions, and semielassical Landauer Buttiker formula. In practice, this recipe enhances the applicability of semiclassical methods to multi-dimensional quantum systems bounded by general soft potentials.展开更多
As the growing interest of web recommendation systems those are applied to deliver customized data for their users, we started working on this system. Generally the recommendation systems are divided into two major ca...As the growing interest of web recommendation systems those are applied to deliver customized data for their users, we started working on this system. Generally the recommendation systems are divided into two major categories such as collaborative recommendation system and content based recommendation system. In case of collaborative recommendation systems, these try to seek out users who share same tastes that of given user as well as recommends the websites according to the liking given user. Whereas the content based recommendation systems tries to recommend web sites similar to those web sites the user has liked. In the recent research we found that the efficient technique based on association rule mining algorithm is proposed in order to solve the problem of web page recommendation. Major problem of the same is that the web pages are given equal importance. Here the importance of pages changes according to the frequency of visiting the web page as well as amount of time user spends on that page. Also recommendation of newly added web pages or the pages that are not yet visited by users is not included in the recommendation set. To overcome this problem, we have used the web usage log in the adaptive association rule based web mining where the association rules were applied to personalization. This algorithm was purely based on the Apriori data mining algorithm in order to generate the association rules. However this method also suffers from some unavoidable drawbacks. In this paper we are presenting and investigating the new approach based on weighted Association Rule Mining Algorithm and text mining. This is improved algorithm which adds semantic knowledge to the results, has more efficiency and hence gives better quality and performances as compared to existing approaches.展开更多
Simultaneous perturbation stochastic approximation （SPSA） belongs to the class of gradient-free optimization methods that extract gradient information from successive objective function evaluation. This paper descri...Simultaneous perturbation stochastic approximation （SPSA） belongs to the class of gradient-free optimization methods that extract gradient information from successive objective function evaluation. This paper describes an improved SPSA algorithm, which entails fuzzy adaptive gain sequences, gradient smoothing, and a step rejection procedure to enhance convergence and stability. The proposed fuzzy adaptive simultaneous perturbation approximation （FASPA） algorithm is particularly well suited to problems involving a large number of parameters such as those encountered in nonlinear system identification using neural networks （NNs）. Accordingly, a multilayer perceptron （MLP） network with popular training algorithms was used to predicate the system response. We found that an MLP trained by FASPSA had the desired accuracy that was comparable to results obtained by traditional system identification algorithms. Simulation results for typical nonlinear systems demonstrate that the proposed NN architecture trained with FASPSA yields improved system identification as measured by reduced time of convergence and a smaller identification error.展开更多
In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling struct...In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling structures,non-linear and time-varying characteristics,so it is a challenge to establish a reliable prediction model.The belief rule base(BRB)can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities.Since each indicator of the complex system can reflect the health state to some extent,the BRB is built based on the causal relationship between system indicators and the health state to achieve the prediction.A health state prediction model based on BRB and long short term memory for complex systems is proposed in this paper.Firstly,the LSTMis introduced to predict the trend of the indicators in the system.Secondly,the Density Peak Clustering(DPC)algorithmis used todetermine referential values of indicators for BRB,which effectively offset the lack of expert knowledge.Then,the predicted values and expert knowledge are fused to construct BRB to predict the health state of the systems by inference.Finally,the effectiveness of the model is verified by a case study of a certain vehicle hydraulic pump.展开更多
The Apriori algorithm is a classical method of association rules mining.Based on analysis of this theory,the paper provides an improved Apriori algorithm.The paper puts foward with algorithm combines HASH table techni...The Apriori algorithm is a classical method of association rules mining.Based on analysis of this theory,the paper provides an improved Apriori algorithm.The paper puts foward with algorithm combines HASH table technique and reduction of candidate item sets to enhance the usage efficiency of resources as well as the individualized service of the data library.展开更多
The mathematical topological rule was applied to plot the predominance area diagram.Based on the analysis of the mutually conjugated,only two diagrams were the best topological embryonic graphs to build the predominan...The mathematical topological rule was applied to plot the predominance area diagram.Based on the analysis of the mutually conjugated,only two diagrams were the best topological embryonic graphs to build the predominance area diagram of Me-S-O system.Combined with topological rules and thermodynamic calculation,four relation-diagrams were denoted asαandβstable and unstable plane-topological diagrams,which were plotted for the Pb-S-O system and Zn-S-O system.The results show thatβstable plane-topological diagram of Pb-S-O system andαstable one of Zn-S-O system are in accordance with the traditional predominance area diagram,which indicates that it is feasible to plot the predominance area diagram based on mathematical topological rules.Meanwhile,αunstable plane-topological diagram of Pb-S-O system can elucidate the phenomenon that metallic lead exists in higher oxygen and sulfur pressure area in modern bath smelting furnace.The mathematical topological rules broaden the application scope of the predominance area diagram and enrich the practice of its plotting.展开更多
Cancelled the first axiom L1) or the third axiom L3) of the classical formal logic system we established two kinds of quasi-formal deductive system, LG-R^* and LG^* respectively. In LG-R^* we proved that neither the d...Cancelled the first axiom L1) or the third axiom L3) of the classical formal logic system we established two kinds of quasi-formal deductive system, LG-R^* and LG^* respectively. In LG-R^* we proved that neither the deduction theorem nor the hypothetical syllogism (HS) rule held but a deduction theorem and an HS rule are obtained in a weak sense. We also proved that both the deduction theorem and the hypothetical syllogism(HS) rule hold in LG^*.展开更多
A two-layer switching architecture and a two-layer switching rule for stabilization of switched linear control systems are proposed, under which the mismatched switching between switched systems and their candidate hy...A two-layer switching architecture and a two-layer switching rule for stabilization of switched linear control systems are proposed, under which the mismatched switching between switched systems and their candidate hybrid controllers can be allowed. In the low layer, a state-dependent switching rule with a dwell time constraint to exponentially stabilize switched linear systems is given; in the high layer, supervisory conditions on the mismatched switching frequency and the mismatched switching ratio are presented, under which the closed-loop switched system is still exponentially stable in case of the candidate controller switches delay with respect to the subsystems. Different from the traditional switching rule, the two-layer switching architecture and switching rule have robustness, which in some extend permit mismatched switching between switched subsystems and their candidate controllers.展开更多
基金supported by King Abdullah University of Science and Technology(KAUST).
文摘We consider various tasks of recognizing properties of DRSs(Decision Rule Systems)in this paper.As solution algorithms,DDTs(Deterministic Decision Trees)and NDTs(Nondeterministic Decision Trees)are used.An NDT can be considered as a representation of a DRS that satisfies the conditions of the considered task and covers all potential inputs.It has been shown that the minimum depth of a DDT solving the task does not exceed the square of the minimum depth of an NDT.The growth of the minimum number of nodes in DDTs and NDTs can be exponential with the size of the original DRSs.There-fore,in the general case,it is better to simulate the behavior of the DT(Deci-sion Tree)on the given tuple of feature values rather than building the entire tree.We propose a greedy algorithm for such modeling and study its efficiency for a class of tasks of recognizing properties of DRSs.The obtained results may be of interest for data analysis in which both DRSs and DTs are intensively studied.In particular,these results make one think about the possibilities of transforming DRSs into DTs.
文摘The research aimed to construct an intelligent review system for construction projects based on Building Information Modeling(BIM)and rule engines.By establishing a BIM data standard system and utilizing Structured Naming Language(SNL)to formalize review rules,combined with model visualization and scene recognition technology,a cloud native platform with automated review capabilities has been developed.The pilot application shows that the system can effectively improve the efficiency and accuracy of planning and construction drawing review,providing a feasible technical solution for digital engineering review.
基金Project(2011AA061003)supported by the High-tech Research and Development Program of China
文摘The mathematical topological rule was proposed to plot the predominance area diagram.Based on the phase rules,the components of In-S-O system were analyzed and the coexisting points of three condensed phases were determined.Combined with the topological rules and thermody namic calculation,four relation diagrams between the coexisting points of three condensed phases,which were denoted as α,β stable plane-topological diagram and unstable plane-topological diagram,were plotted for the In-S-O system.The results show that α stable plane topological diagram is in accordance with the predominance area diagram of In-S-O system plotted by traditional methods,which indicates that the new method is feasible to plot the predominance area diagram of In-S-O system.Meanwhile,β unstable plane-topological diagram can be used to elucidate the indium production with the bath smelting process.
文摘Association rules are useful for determining correlations between items. Applying association rules to intrusion detection system (IDS) can improve the detection rate, but false positive rate is also increased. Weighted association rules are used in this paper to mine intrustion models, which can increase the detection rate and decrease the false positive rate by some extent. Based on this, the structure of host-based IDS using weighted association rules is proposed.
文摘Expert systems (ESs) are being increasingly applied to the fault diagnosis of engines. Based on the idea of ES template (EST), an object-oriented rule-type EST is emphatically studied on such aspects as the object-oriented knowledge representation, the heuristic inference engine with an improved depth-first search (DFS) and the graphical user interface. A diagnositic ES instance for debris on magnetic chip detectors (MCDs) is then created with the EST. The spot running shows that the rule-type EST enhances the abilities of knowledge representation and heuristic inference, and breaks a new way for the rapid construction and implementation of ES.
文摘By the analysis of CORBA technology, distributed technology, multi agent, fuzzy cluster, OA system, expert system and decision support technology, a distributed OA expert system model based on fuzzy rules (DOAES) is proposed. In DOAES, the knowledge and experience of decision makers are processed and transferred into the knowledge base. So the system has the adaptive ability and re study function and the decision results are more scientific and more objective. The DOAES is successfully applied in the management system of invest promotion.
基金the National High-tech Research and Development Program of China(No.2011AA7053016)National Natural Science Foundation of China(No.61174030)
文摘Real-time and accurate fault detection is essential to enhance the aircraft navigation system’s reliability and safety. The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults. On account of this reason, we propose an online detection solution based on non-analytical model. In this article, the navigation system fault detection model is established based on belief rule base （BRB）, where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output. To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update, a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization （EM） algorithm. Furthermore, the proposed method is verified by navigation experiment. Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model. The output of the detection model can track the fault state very well, and the faults can be diagnosed in real time and accurately. In addition, the detection ability, especially in the probability of false detection, is superior to offline optimization method, and thus the system reliability has great improvement.
基金Sponsored by the Science Foundation for Youths of Heilongjiang province (Grant No.QC08C05)
文摘For real-time and distributed features of multi-robot system,the strategy of combining the improved artificial potential field method and the rules based on priority is proposed to study the collision avoidance planning in multi-robot systems. The improved artificial potential field based on simulated annealing algorithm satisfactorily overcomes the drawbacks of traditional artificial potential field method,so that robots can find a local collision-free path in the complex environment. According to the movement vector trail of robots,collisions between robots can be detected,thereby the collision avoidance rules can be obtained. Coordination between robots by the priority based rules improves the real-time property of multi-robot system. The combination of these two methods can help a robot to find a collision-free path from a starting point to the goal quickly in an environment with many obstacles. The feasibility of the proposed method is validated in the VC-based simulated environment.
基金Projects(10871031, 60474070) supported by the National Natural Science Foundation of ChinaProject(07A001) supported by the Scientific Research Fund of Hunan Provincial Education Department, China
文摘Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence were redefined. The algorithm can mine the association rules with decision attributes directly without processing missing values. Using the incomplete dataset Mushroom from UCI machine learning repository, the new algorithm was compared with the classical association rules mining algorithm based on Apriori from the number of rules extracted, testing accuracy and execution time. The experiment results show that the new algorithm has advantages of short execution time and high accuracy.
文摘In new environments of trading, customer's trust is vital for the extended progress and development of electronic commerce. This paper proposes that in addition to known factors of electronic commerce B2C websites such a design of websites, security of websites and familiarity of website influence customers trust in online transactions. This paper presents an application of expert system on trust in electronic commerce. Based on experts’ judgment, a frame of work was proposed. The proposed model applies ANFIS and Mamdani inference fuzzy system to get the desired results and then results of two methods were compared. Two questionnaires were used in this study. The first questionnaire was developed for e-commerce experts, and the second one was designed for the customers of electronic websites. Based on AHP method, Expert Choice software was used to determine the priority of factors in the first questionnaire, and MATLAB and Excel were used for developing the fuzzy rules. Finally, the fuzzy logical kit was used to analyze the generated factors in the model. Our study findings show that trust in EC transactions is strongly mediated by perceived security.
基金supported by the National Natural Science Foundation of China (61070241)the Natural Science Foundation of Shandong Province (ZR2010FM035)Science Research Foundation of University of Jinan (XKY0808)
文摘A new approach to knowledge acquisition in incomplete information system with fuzzy decisions is proposed. In such incomplete information system, the universe of discourse is classified by the maximal tolerance classes, and fuzzy approximations are defined based on them. Three types of relative reducts of maximal tolerance classes are then proposed, and three types of fuzzy decision rules based on the proposed attribute description are defined. The judgment theorems and approximation discernibility functions with respect to them are presented to compute the relative reduct by using Boolean reasoning techniques, from which we can derive optimal fuzzy decision rules from the systems. At last, three types of relative reducts of the system and their computing methods are given.
基金supported by the National Natural Science Foundation of China(61473176,61402260,61573225)the Natural Science Foundation of Shandong Province for Outstanding Young Talents in Provincial Universities(ZR2015JL021,ZR2015JL003)the Open Program from the State Key Laboratory of Management and Control for Complex Systems(20140102)
文摘Wind is one kind of clean and free renewable energy sources. Wind speed plays a pivotal role in the wind power output. However, due to the random and unstable nature of the wind, accurate prediction of wind speed is a particularly challenging task. This paper presents a novel neural fuzzy method for the hourly wind speed prediction. Firstly, a neural structure is proposed for the functional-type single-input-rule-modules(FSIRMs) connected fuzzy inference system(FIS) to combine the merits of both the FSIRMs connected FIS and the neural network. Then, in order to achieve both the smallest training errors and the smallest parameters, a least square method based parameter learning algorithm is presented for the proposed FSIRMs connected neural fuzzy system(FSIRMNFS). Further,the proposed FSIRMNFS and its parameter learning algorithm are applied to the hourly wind speed prediction. Experiments and comparisons are also made to show the effectiveness and advantages of the proposed approach. Experimental results verified that our study has presented an effective approach for the hourly wind speed prediction. The proposed approach can also be used for the prediction of wind direction, wind power and some other prediction applications in the research field of renewable energy.
基金Supported by the National Science Council at Taiwan through Grants No. NSC 97-2112-M-009-008-MY3
文摘While the scattering phase for several one-dimensional potentials can be exactly derived, less is known in multi-dimensional quantum systems. This work provides a method to extend the one-dimensional phase knowledge to multi-dimensional quantization rules. The extension is illustrated in the example of Bogomolny＇s transfer operator method applied in two quantum wells bounded by step potentials of different heights. This generalized semiclassical method accurately determines the energy spectrum of the systems, which indicates the substantial role of the proposed phase correction. Theoretically, the result can be extended to other semiclassical methods, such as Gutzwiller trace formula, dynamical zeta functions, and semielassical Landauer Buttiker formula. In practice, this recipe enhances the applicability of semiclassical methods to multi-dimensional quantum systems bounded by general soft potentials.
文摘As the growing interest of web recommendation systems those are applied to deliver customized data for their users, we started working on this system. Generally the recommendation systems are divided into two major categories such as collaborative recommendation system and content based recommendation system. In case of collaborative recommendation systems, these try to seek out users who share same tastes that of given user as well as recommends the websites according to the liking given user. Whereas the content based recommendation systems tries to recommend web sites similar to those web sites the user has liked. In the recent research we found that the efficient technique based on association rule mining algorithm is proposed in order to solve the problem of web page recommendation. Major problem of the same is that the web pages are given equal importance. Here the importance of pages changes according to the frequency of visiting the web page as well as amount of time user spends on that page. Also recommendation of newly added web pages or the pages that are not yet visited by users is not included in the recommendation set. To overcome this problem, we have used the web usage log in the adaptive association rule based web mining where the association rules were applied to personalization. This algorithm was purely based on the Apriori data mining algorithm in order to generate the association rules. However this method also suffers from some unavoidable drawbacks. In this paper we are presenting and investigating the new approach based on weighted Association Rule Mining Algorithm and text mining. This is improved algorithm which adds semantic knowledge to the results, has more efficiency and hence gives better quality and performances as compared to existing approaches.
文摘Simultaneous perturbation stochastic approximation （SPSA） belongs to the class of gradient-free optimization methods that extract gradient information from successive objective function evaluation. This paper describes an improved SPSA algorithm, which entails fuzzy adaptive gain sequences, gradient smoothing, and a step rejection procedure to enhance convergence and stability. The proposed fuzzy adaptive simultaneous perturbation approximation （FASPA） algorithm is particularly well suited to problems involving a large number of parameters such as those encountered in nonlinear system identification using neural networks （NNs）. Accordingly, a multilayer perceptron （MLP） network with popular training algorithms was used to predicate the system response. We found that an MLP trained by FASPSA had the desired accuracy that was comparable to results obtained by traditional system identification algorithms. Simulation results for typical nonlinear systems demonstrate that the proposed NN architecture trained with FASPSA yields improved system identification as measured by reduced time of convergence and a smaller identification error.
基金supported by the Natural Science Foundation of China underGrant 61833016 and 61873293the Shaanxi OutstandingYouth Science Foundation underGrant 2020JC-34the Shaanxi Science and Technology Innovation Team under Grant 2022TD-24.
文摘In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling structures,non-linear and time-varying characteristics,so it is a challenge to establish a reliable prediction model.The belief rule base(BRB)can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities.Since each indicator of the complex system can reflect the health state to some extent,the BRB is built based on the causal relationship between system indicators and the health state to achieve the prediction.A health state prediction model based on BRB and long short term memory for complex systems is proposed in this paper.Firstly,the LSTMis introduced to predict the trend of the indicators in the system.Secondly,the Density Peak Clustering(DPC)algorithmis used todetermine referential values of indicators for BRB,which effectively offset the lack of expert knowledge.Then,the predicted values and expert knowledge are fused to construct BRB to predict the health state of the systems by inference.Finally,the effectiveness of the model is verified by a case study of a certain vehicle hydraulic pump.
文摘The Apriori algorithm is a classical method of association rules mining.Based on analysis of this theory,the paper provides an improved Apriori algorithm.The paper puts foward with algorithm combines HASH table technique and reduction of candidate item sets to enhance the usage efficiency of resources as well as the individualized service of the data library.
基金Project(2011AA061003) supported by the High-Tech Research and Development Program of China
文摘The mathematical topological rule was applied to plot the predominance area diagram.Based on the analysis of the mutually conjugated,only two diagrams were the best topological embryonic graphs to build the predominance area diagram of Me-S-O system.Combined with topological rules and thermodynamic calculation,four relation-diagrams were denoted asαandβstable and unstable plane-topological diagrams,which were plotted for the Pb-S-O system and Zn-S-O system.The results show thatβstable plane-topological diagram of Pb-S-O system andαstable one of Zn-S-O system are in accordance with the traditional predominance area diagram,which indicates that it is feasible to plot the predominance area diagram based on mathematical topological rules.Meanwhile,αunstable plane-topological diagram of Pb-S-O system can elucidate the phenomenon that metallic lead exists in higher oxygen and sulfur pressure area in modern bath smelting furnace.The mathematical topological rules broaden the application scope of the predominance area diagram and enrich the practice of its plotting.
文摘Cancelled the first axiom L1) or the third axiom L3) of the classical formal logic system we established two kinds of quasi-formal deductive system, LG-R^* and LG^* respectively. In LG-R^* we proved that neither the deduction theorem nor the hypothetical syllogism (HS) rule held but a deduction theorem and an HS rule are obtained in a weak sense. We also proved that both the deduction theorem and the hypothetical syllogism(HS) rule hold in LG^*.
基金supported by the National Natural Science Foundation of China(No.61233002)the Fundamental Research Funds for the Central Universities(No.N120404019)
文摘A two-layer switching architecture and a two-layer switching rule for stabilization of switched linear control systems are proposed, under which the mismatched switching between switched systems and their candidate hybrid controllers can be allowed. In the low layer, a state-dependent switching rule with a dwell time constraint to exponentially stabilize switched linear systems is given; in the high layer, supervisory conditions on the mismatched switching frequency and the mismatched switching ratio are presented, under which the closed-loop switched system is still exponentially stable in case of the candidate controller switches delay with respect to the subsystems. Different from the traditional switching rule, the two-layer switching architecture and switching rule have robustness, which in some extend permit mismatched switching between switched subsystems and their candidate controllers.
