This paper presents a new approach for detection and classification of various power signal disturbances, which constitute an important aspect of power quality assessment. A frequency filtering fast S-transform algorithm is developed with different types of frequency scaling, bandpass filtering and interpolation techniques to reduce the computational cost. The new time-frequency transform based on dyadic scaling has been used for the extraction of relevant features from the power quality disturbance signals. The extracted features are then passed through a decision tree based classifier for the identification of the disturbance patterns. Various simultaneous power signal disturbances have been simulated to prove the efficiency of the technique. The simulation results show superior performance of the new frequency filtering S-transform while classifying overlapping disturbance patterns. Because of the frequency filtering dyadic S-transform algorithm and a relatively simpler classifier methodology, this technique can be used for real time localization, detection, and classification of various power quality events.
{"title":"A hybrid decision tree and new frequency filtering S-transform for simultaneous power signal disturbance pattern recognition","authors":"R. Bisoi, P. Dash, P. Nayak","doi":"10.3233/KES-140301","DOIUrl":"https://doi.org/10.3233/KES-140301","url":null,"abstract":"This paper presents a new approach for detection and classification of various power signal disturbances, which constitute an important aspect of power quality assessment. A frequency filtering fast S-transform algorithm is developed with different types of frequency scaling, bandpass filtering and interpolation techniques to reduce the computational cost. The new time-frequency transform based on dyadic scaling has been used for the extraction of relevant features from the power quality disturbance signals. The extracted features are then passed through a decision tree based classifier for the identification of the disturbance patterns. Various simultaneous power signal disturbances have been simulated to prove the efficiency of the technique. The simulation results show superior performance of the new frequency filtering S-transform while classifying overlapping disturbance patterns. Because of the frequency filtering dyadic S-transform algorithm and a relatively simpler classifier methodology, this technique can be used for real time localization, detection, and classification of various power quality events.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116591555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Recent years have witnessed a rapid growth in the quantity of Arabic-formulated information available in electronic format on both the Internet and corporate intranet. As a result, the user turns out to be overwhelmed by such a huge mass of information, with an arising question of how to locate or retrieve the desired information they need. For this end, several automatic classification systems have been developed both on the Internet, and within companies. With respect to the present paper, a special attempt is made to present a thorough examination of the effectiveness of applying a specific machine-learning technique relevant to help solve the Arabic text related classification problem. In addition, we undertake to explore and identify the major Hidden Markov Model (HMM) classifier benefits with regard to Arabic text classification procedure based on our newly-designed stemming approach. On the basis of the reached experimental results, one might well notice that our conceived HMM-based model has managed to achieve a high-classification accuracy with regard to Arabic-electronic text corpuses.
{"title":"A new-arabic-text classification system using a Hidden Markov Model","authors":"Zied Kechaou, S. Kanoun","doi":"10.3233/KES-140297","DOIUrl":"https://doi.org/10.3233/KES-140297","url":null,"abstract":"The Recent years have witnessed a rapid growth in the quantity of Arabic-formulated information available in electronic format on both the Internet and corporate intranet. As a result, the user turns out to be overwhelmed by such a huge mass of information, with an arising question of how to locate or retrieve the desired information they need. For this end, several automatic classification systems have been developed both on the Internet, and within companies. With respect to the present paper, a special attempt is made to present a thorough examination of the effectiveness of applying a specific machine-learning technique relevant to help solve the Arabic text related classification problem. In addition, we undertake to explore and identify the major Hidden Markov Model (HMM) classifier benefits with regard to Arabic text classification procedure based on our newly-designed stemming approach. On the basis of the reached experimental results, one might well notice that our conceived HMM-based model has managed to achieve a high-classification accuracy with regard to Arabic-electronic text corpuses.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134439421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The concept of mutually exclusive hypothesis graph (MEHG) is introduced and NP-completeness of several problems on MEHG is proved. A probabilistic search algorithm is proposed for finding suboptimal branchings in such graphs and its performance is evaluated for graphs with uniform and exponential weight distribution.
{"title":"A probabilistic search algorithm for finding suboptimal branchings in mutually exclusive hypothesis graph","authors":"M. V. Davydov","doi":"10.3233/KES-140302","DOIUrl":"https://doi.org/10.3233/KES-140302","url":null,"abstract":"The concept of mutually exclusive hypothesis graph (MEHG) is introduced and NP-completeness of several problems on MEHG is proved. A probabilistic search algorithm is proposed for finding suboptimal branchings in such graphs and its performance is evaluated for graphs with uniform and exponential weight distribution.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"211 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114341414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The quality of stainless steel weld is highly influenced by delta ferrite content expressed in terms of ferrite number. The quantity of delta ferrite content formed is controlled by the process parameters. This paper discusses the development of artificial neural network model for predicting the ferrite number in 202 grade stainless steel gas tungsten arc welded plates (GTAW). The process parameters chosen for study are welding gun angle, welding speed, plate length, welding current and shielding gas flow rate. The experiments were conducted based on design of experiments fractional factorial with 125 runs. Using the experimental data, feed forward, back propagation neural models were developed and trained using Levenberg Marquardt algorithm. The training, learning, performance and transfer functions used are trainlm, learningdm, mean square error and tansig respectively. Five networks were developed with five neurons in the input layer, 1 neuron in the output layer and different nodes in the hidden layer. They are 5-3-1, 5-5-1, 5-10-1, 5-11-1 and 5-15-1. It was found that the artificial neural network (ANN) model based on network 5-5-1 predicted ferrite number more accurately than other networks. The prediction helps in identifying the recommended combination of process parameters to achieve a desired ferrite number in GTAW of stainless steel 202 grade plates.
{"title":"Prediction of ferrite number in stainless steel gas tungsten arc welded plates using artificial neural networks","authors":"R. Sudhakaran, P. S. Sivasakthivel","doi":"10.3233/KES-140298","DOIUrl":"https://doi.org/10.3233/KES-140298","url":null,"abstract":"The quality of stainless steel weld is highly influenced by delta ferrite content expressed in terms of ferrite number. The quantity of delta ferrite content formed is controlled by the process parameters. This paper discusses the development of artificial neural network model for predicting the ferrite number in 202 grade stainless steel gas tungsten arc welded plates (GTAW). The process parameters chosen for study are welding gun angle, welding speed, plate length, welding current and shielding gas flow rate. The experiments were conducted based on design of experiments fractional factorial with 125 runs. Using the experimental data, feed forward, back propagation neural models were developed and trained using Levenberg Marquardt algorithm. The training, learning, performance and transfer functions used are trainlm, learningdm, mean square error and tansig respectively. Five networks were developed with five neurons in the input layer, 1 neuron in the output layer and different nodes in the hidden layer. They are 5-3-1, 5-5-1, 5-10-1, 5-11-1 and 5-15-1. It was found that the artificial neural network (ANN) model based on network 5-5-1 predicted ferrite number more accurately than other networks. The prediction helps in identifying the recommended combination of process parameters to achieve a desired ferrite number in GTAW of stainless steel 202 grade plates.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124378046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We concern the issue of preference recommendation towards more reliable recommender system. General recommender system provides a collection of items or several bests of them, on the basis of a fixed preference constraint. However, the realistic preference from users may be such complicated that makes conventional recommender system unreliable. In real-world applications, e.g. travel planning or hotel selection, specific constraints may be involved like a limited travel time or an appropriate budget for hotel accommodation. Motivated by these applications, we investigate the constrained preference recommendation (CPR), in which two main types are studied including Threshold-CPR (T-CPR) and Range-CPR (R-CPR). We firstly analyze and define the related problems. Then, we provide solutions with illustration of problem-solving procedure. The results are analogized with other representative techniques. Finally, we provide an extension study on the general CPR problems. Therein, we firstly provide a normalized system for constraint representation. Secondly, we utilize the proposed normalized system to analyze representative literature.
{"title":"Evaluation of constrained preference recommendation","authors":"Anming Li, J. Chai","doi":"10.3233/KES-140295","DOIUrl":"https://doi.org/10.3233/KES-140295","url":null,"abstract":"We concern the issue of preference recommendation towards more reliable recommender system. General recommender system provides a collection of items or several bests of them, on the basis of a fixed preference constraint. However, the realistic preference from users may be such complicated that makes conventional recommender system unreliable. In real-world applications, e.g. travel planning or hotel selection, specific constraints may be involved like a limited travel time or an appropriate budget for hotel accommodation. Motivated by these applications, we investigate the constrained preference recommendation (CPR), in which two main types are studied including Threshold-CPR (T-CPR) and Range-CPR (R-CPR). We firstly analyze and define the related problems. Then, we provide solutions with illustration of problem-solving procedure. The results are analogized with other representative techniques. Finally, we provide an extension study on the general CPR problems. Therein, we firstly provide a normalized system for constraint representation. Secondly, we utilize the proposed normalized system to analyze representative literature.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133493093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emmanouil I. Marakakis, H. Kondylakis, N. Papadakis
This paper presents an interactive verifier for logic programs. These logic programs are constructed by a schema-based method. Each program is associated with proof schemes due to the program development method. The correctness proof of a program is guided by its associated proof schemes. The main components of the verifier are the prover which carries out the proof steps, the knowledge base (KB) which includes representations of all theories and transformation rules, the KB update which supports the update of KB and the graphical user interface (GUI). The emphasis in the design of this proof checker is on effective guidance of the proof based on the activated proof schemes and on performance by the verifier of tedious, trivial and time consuming tasks. The difficult proof decisions are taken by the user, then, the proof checker applies them. The design of the interface is based on providing the user the required support for the proof of a theorem and for the update of KB. This system is an effective and useful tool for the interactive verification of non-trivial logic programs.
{"title":"A knowledge-based interactive verifier for logic programs","authors":"Emmanouil I. Marakakis, H. Kondylakis, N. Papadakis","doi":"10.3233/KES-140294","DOIUrl":"https://doi.org/10.3233/KES-140294","url":null,"abstract":"This paper presents an interactive verifier for logic programs. These logic programs are constructed by a schema-based method. Each program is associated with proof schemes due to the program development method. The correctness proof of a program is guided by its associated proof schemes. The main components of the verifier are the prover which carries out the proof steps, the knowledge base (KB) which includes representations of all theories and transformation rules, the KB update which supports the update of KB and the graphical user interface (GUI). The emphasis in the design of this proof checker is on effective guidance of the proof based on the activated proof schemes and on performance by the verifier of tedious, trivial and time consuming tasks. The difficult proof decisions are taken by the user, then, the proof checker applies them. The design of the interface is based on providing the user the required support for the proof of a theorem and for the update of KB. This system is an effective and useful tool for the interactive verification of non-trivial logic programs.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"53 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134364176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of security checks at airports is to achieve a reduction in the risk of malevolent attacks on the aviation system. The introduction of new security measures aims at reducing this perceived level of risk, and often takes place as a direct reaction to (attempted) attacks. This procedure means that offenders remain one step ahead of security agents. The aim of the approach presented here is to overcome this shortfall by supporting decision-making in the context of airport security by a systematically created knowledge base. The combination of two well-accepted methods scenario analysis and structural complexity management supports a structured knowledge acquisition process that serves as a basis for the proactive identification of system weaknesses. Furthermore, this combination of methods can be applied to the search for optimisation potentials concerned with possible future threats. The basis for the approach is composed of threat scenario components, security measures and dependencies between these elements. A Multiple-Domain Matrix is applied for system modelling. Clustering of threat scenarios and intensity of relations to security measures are used for analysis. The interpretation of findings makes use of portfolio representations.
{"title":"Managing complex socio-technical systems: A proactive approach to airport security","authors":"M. Cole, M. Maurer","doi":"10.3233/KES-140300","DOIUrl":"https://doi.org/10.3233/KES-140300","url":null,"abstract":"The purpose of security checks at airports is to achieve a reduction in the risk of malevolent attacks on the aviation system. The introduction of new security measures aims at reducing this perceived level of risk, and often takes place as a direct reaction to (attempted) attacks. This procedure means that offenders remain one step ahead of security agents. The aim of the approach presented here is to overcome this shortfall by supporting decision-making in the context of airport security by a systematically created knowledge base. The combination of two well-accepted methods scenario analysis and structural complexity management supports a structured knowledge acquisition process that serves as a basis for the proactive identification of system weaknesses. Furthermore, this combination of methods can be applied to the search for optimisation potentials concerned with possible future threats. The basis for the approach is composed of threat scenario components, security measures and dependencies between these elements. A Multiple-Domain Matrix is applied for system modelling. Clustering of threat scenarios and intensity of relations to security measures are used for analysis. The interpretation of findings makes use of portfolio representations.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131180989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, Bayesian Network has become an important modeling method for decision making problems of real-world applications. In this paper learning parameters of a fuzzy Bayesian Network (BN) based on imprecise/fuzzy observations is considered, where imprecise observations particularly refers to triangular fuzzy numbers. To achieve this, an extension to fuzzy probability theory based on imprecise observations is proposed which employs both the "truth" concept of Yager and the Extension Principle in fuzzy set theory. In addition, some examples are given to demonstrate the concepts of the proposed idea. The aim of our suggestion is to be able to estimate joint fuzzy probability and the conditional probability tables (CPTs) of Bayesian Network based on imprecise observations. Two real-world datasets, Car Evaluation Database (CED) and Extending Credibility (EC), are employed where some of attributes have crisp (exact) and some of them have fuzzy observations. Estimated parameters of the CED's corresponding network, using our extension, are shown in tables. Then, using Kullback-Leibler divergence, two scenarios are considered to show that fuzzy parameters preserve more knowledge than that of crisp parameters. This phenomenon is also true in cases where there are a small number of observations. Finally, to examine a network with fuzzy parameters versus the network with crisp parameters, accuracy result of predictions is provided which shows improvements in the predictions.
{"title":"Learning parameters of fuzzy Bayesian Network based on imprecise observations","authors":"M. G. Ahsaee, Mahmoud Naghibzadeh, B. S. Gildeh","doi":"10.3233/KES-140296","DOIUrl":"https://doi.org/10.3233/KES-140296","url":null,"abstract":"In recent years, Bayesian Network has become an important modeling method for decision making problems of real-world applications. In this paper learning parameters of a fuzzy Bayesian Network (BN) based on imprecise/fuzzy observations is considered, where imprecise observations particularly refers to triangular fuzzy numbers. To achieve this, an extension to fuzzy probability theory based on imprecise observations is proposed which employs both the \"truth\" concept of Yager and the Extension Principle in fuzzy set theory. In addition, some examples are given to demonstrate the concepts of the proposed idea. The aim of our suggestion is to be able to estimate joint fuzzy probability and the conditional probability tables (CPTs) of Bayesian Network based on imprecise observations. Two real-world datasets, Car Evaluation Database (CED) and Extending Credibility (EC), are employed where some of attributes have crisp (exact) and some of them have fuzzy observations. Estimated parameters of the CED's corresponding network, using our extension, are shown in tables. Then, using Kullback-Leibler divergence, two scenarios are considered to show that fuzzy parameters preserve more knowledge than that of crisp parameters. This phenomenon is also true in cases where there are a small number of observations. Finally, to examine a network with fuzzy parameters versus the network with crisp parameters, accuracy result of predictions is provided which shows improvements in the predictions.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125879704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A generalized Bayesian inference nets model (GBINM) to aid developers to construct self-adaptive Bayesian inference nets for various applications and a new approach of defining and assigning statistical parameters to Bayesian inference nodes needed to calculate propagation of probabilities and address uncertainties are proposed. GBINM and the proposed approach are applied to design an intelligent medical system to diagnose cardiovascular diseases. Thousands of site-sampled clinical data are used for designing and testing such a constructed system. The preliminary diagnostic results show that the proposed methodology has salient validity and effectiveness
{"title":"Self-adaptive Bayesian fuzzy inference nets to diagnose cardiovascular diseases","authors":"B. Sekar, M. Dong","doi":"10.3233/KES-140299","DOIUrl":"https://doi.org/10.3233/KES-140299","url":null,"abstract":"A generalized Bayesian inference nets model (GBINM) to aid developers to construct self-adaptive Bayesian inference nets for various applications and a new approach of defining and assigning statistical parameters to Bayesian inference nodes needed to calculate propagation of probabilities and address uncertainties are proposed. GBINM and the proposed approach are applied to design an intelligent medical system to diagnose cardiovascular diseases. Thousands of site-sampled clinical data are used for designing and testing such a constructed system. The preliminary diagnostic results show that the proposed methodology has salient validity and effectiveness","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"24 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121011670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the article is proposed and analyzed the usage of ontological models for facilitating the execution of tasks of complex ontology management, such as ontology creation, modification, elements provenance tracing and validation. Methods for applying ontological task models to assist ontology management are developed and ensuing advantages are highlighted. Software prototype of modeling environment is described.
{"title":"Complex ontology management using task models","authors":"Eugene Burov","doi":"10.3233/KES-140291","DOIUrl":"https://doi.org/10.3233/KES-140291","url":null,"abstract":"In the article is proposed and analyzed the usage of ontological models for facilitating the execution of tasks of complex ontology management, such as ontology creation, modification, elements provenance tracing and validation. Methods for applying ontological task models to assist ontology management are developed and ensuing advantages are highlighted. Software prototype of modeling environment is described.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"3395 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127501659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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