Pub Date : 2012-07-01DOI: 10.1504/IJAISC.2012.048178
S. S. Gill, R. Chandel, A. Chandel
In this paper circuit netlist bipartitioning using particle swarm optimisation technique is presented. Particle swarm optimisation is a powerful evolutionary computation technique for global search and optimisation. The circuit netlist is partitioned into two partitions such that the number of interconnections between the partitions (cutsize) is minimised. Results obtained show the versatility of the proposed soft computing method in solving non polynomial hard problems like circuit netlist partitioning.
{"title":"Netlist bipartitioning using particle swarm optimisation technique","authors":"S. S. Gill, R. Chandel, A. Chandel","doi":"10.1504/IJAISC.2012.048178","DOIUrl":"https://doi.org/10.1504/IJAISC.2012.048178","url":null,"abstract":"In this paper circuit netlist bipartitioning using particle swarm optimisation technique is presented. Particle swarm optimisation is a powerful evolutionary computation technique for global search and optimisation. The circuit netlist is partitioned into two partitions such that the number of interconnections between the partitions (cutsize) is minimised. Results obtained show the versatility of the proposed soft computing method in solving non polynomial hard problems like circuit netlist partitioning.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134513556","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}
Pub Date : 2012-07-01DOI: 10.1504/IJAISC.2012.048177
A. Chakraborty, T. Bhattacharjee
Fuzzy Logic is known for its applicability in modelling uncertainty and has been applied extensively to model various types of uncertainty in engineering sector. The main objective of this paper is to present a fuzzy approach to power purchases in a deregulated power system. Deregulation of the Electric Supply Industry (ESI) has resulted in electricity being traded as a commodity in the electricity market. However, the spot price of electricity is not known apriori and to generate an optimal power purchase plan, the same has to be estimated with certain degrees of uncertainty. In this paper, an attempt has been made to estimate the same using fuzzy logic. The uncertainty factor of load forecasting is also dealt with using fuzzy membership function in the current study. The results highlight the benefit gained viz. saving of cost owing to strategic drawal.
{"title":"Fuzzy system approach to power purchases in a power pool of a deregulated power system","authors":"A. Chakraborty, T. Bhattacharjee","doi":"10.1504/IJAISC.2012.048177","DOIUrl":"https://doi.org/10.1504/IJAISC.2012.048177","url":null,"abstract":"Fuzzy Logic is known for its applicability in modelling uncertainty and has been applied extensively to model various types of uncertainty in engineering sector. The main objective of this paper is to present a fuzzy approach to power purchases in a deregulated power system. Deregulation of the Electric Supply Industry (ESI) has resulted in electricity being traded as a commodity in the electricity market. However, the spot price of electricity is not known apriori and to generate an optimal power purchase plan, the same has to be estimated with certain degrees of uncertainty. In this paper, an attempt has been made to estimate the same using fuzzy logic. The uncertainty factor of load forecasting is also dealt with using fuzzy membership function in the current study. The results highlight the benefit gained viz. saving of cost owing to strategic drawal.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115379338","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}
Pub Date : 2012-07-01DOI: 10.1504/IJAISC.2012.048176
G. Shen, Yanqing Zhang
The Cutting Stock Problem (CSP) is an integer combinatorial optimisation problem (an NP hard problem). It is an important problem in many industrial applications. In recent years, various traditional algorithms have been applied to the CSP, such as the Linear Programming (LP), the Branch and Cut (BC), the Evolutionary Algorithm (EA), etc. To continue improve performance, this paper proposes a novel Shadow Price based Genetic Algorithm (SPGA) to solve the CSP. The main contribution of this work is to combine distinct methods to generate better solutions. The experimental results have shown that the new SPGA has produced much better solutions than the classic Genetic Algorithm (GA) and other bio-inspired algorithms. This paper also demonstrates the new algorithm's capability of solving multi-objective optimisation problems.
{"title":"Shadow price based genetic algorithms for the cutting stock problem","authors":"G. Shen, Yanqing Zhang","doi":"10.1504/IJAISC.2012.048176","DOIUrl":"https://doi.org/10.1504/IJAISC.2012.048176","url":null,"abstract":"The Cutting Stock Problem (CSP) is an integer combinatorial optimisation problem (an NP hard problem). It is an important problem in many industrial applications. In recent years, various traditional algorithms have been applied to the CSP, such as the Linear Programming (LP), the Branch and Cut (BC), the Evolutionary Algorithm (EA), etc. To continue improve performance, this paper proposes a novel Shadow Price based Genetic Algorithm (SPGA) to solve the CSP. The main contribution of this work is to combine distinct methods to generate better solutions. The experimental results have shown that the new SPGA has produced much better solutions than the classic Genetic Algorithm (GA) and other bio-inspired algorithms. This paper also demonstrates the new algorithm's capability of solving multi-objective optimisation problems.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"17 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130724159","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}
Pub Date : 2012-07-01DOI: 10.1504/IJAISC.2012.048180
M. Saini, Rajiv Kapoor
A novel framework has been proposed by integrating FIM with APSO to get their mutual benefits for achieving near optimum codebook for carrying an image compression. Proposed scheme uses adaptive strategies which have two main features that give APSO an upper hand over the PSO. This FAPSOVQ strategy is compared with FPSOVQ algorithm to show its efficiency in terms of preventing the global best particle from getting stuck in local optima as in the PSO. Peak-signal-to-noise ratio is taking as a parameter to show the efficiency of proposed scheme.
{"title":"Image compression using APSO","authors":"M. Saini, Rajiv Kapoor","doi":"10.1504/IJAISC.2012.048180","DOIUrl":"https://doi.org/10.1504/IJAISC.2012.048180","url":null,"abstract":"A novel framework has been proposed by integrating FIM with APSO to get their mutual benefits for achieving near optimum codebook for carrying an image compression. Proposed scheme uses adaptive strategies which have two main features that give APSO an upper hand over the PSO. This FAPSOVQ strategy is compared with FPSOVQ algorithm to show its efficiency in terms of preventing the global best particle from getting stuck in local optima as in the PSO. Peak-signal-to-noise ratio is taking as a parameter to show the efficiency of proposed scheme.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131080610","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}
Pub Date : 2012-07-01DOI: 10.1504/IJAISC.2012.048179
O. Oladipupo, C. Uwadia, C. Ayo
In this paper, a Fuzzy Association Rule Mining (FARM) with expert-driven approach is proposed to acquire a knowledge-base, which corresponds more intuitively to human perception with a high comprehensibility. This approach reduces the number of rules in the knowledge-base when compared with the Standard Rule-base Formulation (SRF) and makes possible the rating of the rules according to their relevance. The rule relevance is determined by the measures of significance and certainty factors. The approach is validated using a medical database and the result shows that this approach ultimately reduces the number of rules and enhances the comprehensibility of the expert system.
{"title":"Improving medical rule-based expert systems comprehensibility: fuzzy association rule mining approach","authors":"O. Oladipupo, C. Uwadia, C. Ayo","doi":"10.1504/IJAISC.2012.048179","DOIUrl":"https://doi.org/10.1504/IJAISC.2012.048179","url":null,"abstract":"In this paper, a Fuzzy Association Rule Mining (FARM) with expert-driven approach is proposed to acquire a knowledge-base, which corresponds more intuitively to human perception with a high comprehensibility. This approach reduces the number of rules in the knowledge-base when compared with the Standard Rule-base Formulation (SRF) and makes possible the rating of the rules according to their relevance. The rule relevance is determined by the measures of significance and certainty factors. The approach is validated using a medical database and the result shows that this approach ultimately reduces the number of rules and enhances the comprehensibility of the expert system.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"93 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114589814","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}
Pub Date : 2011-09-01DOI: 10.1504/IJAISC.2011.042716
Nada Kherici, Y. M. B. Ali
This paper discusses the bio-inspired algorithm of the Particle Swarm Optimisation (PSO) for a wheeled robot|s displacement. PSO was selected because its flexibility and its tempting results. An omnidirectional wheeled robot was simulated on a flat environment with two tasks: |Reach a goal| or |collect balls|. This paper checks on the performance of PSO for the displacement studied. In the first case, we discussed the variation of execution time compared to the particles| and the neighbours| number. In the second one, we studied the change in the path|s length compared to execution time depending on the particles| and balls| number.
{"title":"Bio-inspired algorithm for wheeled robot's navigation","authors":"Nada Kherici, Y. M. B. Ali","doi":"10.1504/IJAISC.2011.042716","DOIUrl":"https://doi.org/10.1504/IJAISC.2011.042716","url":null,"abstract":"This paper discusses the bio-inspired algorithm of the Particle Swarm Optimisation (PSO) for a wheeled robot|s displacement. PSO was selected because its flexibility and its tempting results. An omnidirectional wheeled robot was simulated on a flat environment with two tasks: |Reach a goal| or |collect balls|. This paper checks on the performance of PSO for the displacement studied. In the first case, we discussed the variation of execution time compared to the particles| and the neighbours| number. In the second one, we studied the change in the path|s length compared to execution time depending on the particles| and balls| number.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129707160","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}
Pub Date : 2011-09-01DOI: 10.1504/IJAISC.2011.042713
M. Sornam, P. Thangavel
An improved Optical Backpropagation (OBP) algorithm for training single hidden layer feedforward neural network with third term is proposed. The major limitations of backpropagation algorithm are the local minima problem and the slow rate of convergence. To solve these problems, we have proposed an algorithm by introducing a third term with optical backpropagation (OBPWT). This method has been applied to the multilayer neural network to improve the efficiency in terms of convergence speed. In the proposed algorithm, a non-linear function on the error term is introduced before applying the backpropagation phase. This error term is used along with a third term in the weight updation rule. We have shown how the new proposed algorithm drastically accelerates the training convergence at the same time maintaining the neural networkâs performance. The effectiveness of the proposed algorithm has been shown by testing five benchmark problems. The simulation results show that the proposed algorithm is capable of speeding up the learning and hence the rate of convergence.
{"title":"An improved three-term optical backpropagation algorithm","authors":"M. Sornam, P. Thangavel","doi":"10.1504/IJAISC.2011.042713","DOIUrl":"https://doi.org/10.1504/IJAISC.2011.042713","url":null,"abstract":"An improved Optical Backpropagation (OBP) algorithm for training single hidden layer feedforward neural network with third term is proposed. The major limitations of backpropagation algorithm are the local minima problem and the slow rate of convergence. To solve these problems, we have proposed an algorithm by introducing a third term with optical backpropagation (OBPWT). This method has been applied to the multilayer neural network to improve the efficiency in terms of convergence speed. In the proposed algorithm, a non-linear function on the error term is introduced before applying the backpropagation phase. This error term is used along with a third term in the weight updation rule. We have shown how the new proposed algorithm drastically accelerates the training convergence at the same time maintaining the neural networkâs performance. The effectiveness of the proposed algorithm has been shown by testing five benchmark problems. The simulation results show that the proposed algorithm is capable of speeding up the learning and hence the rate of convergence.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126098012","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}
Pub Date : 2011-09-01DOI: 10.1504/IJAISC.2011.042717
Bailing Zhang
This paper emphasised an approach for offline signature verification and identification. Two image descriptors are studied, including Pyramid Histogram of Oriented Gradients (PHOG), and a direction feature proposed in the literature. Compared with many previously proposed signature feature extraction approaches, PHOG has advantages in the extraction of discriminative information from handwriting signature images. The significance of classification framework is stressed. With the benchmarking database ||Grupo de Procesado Digital de Senales|| (GPDS), satisfactory performances were obtained from several classifiers. Among the classifiers compared, SVM is clearly superior, giving a False Rejection Rate (FRR) of 2.5% and a False Acceptance Rate (FAR) 2% for skillful forgery, which compares sharply with the latest published results on the same dataset. This substantiates the superiority of the proposed method. The related issue offline signature recognition is also investigated based on the same approach, with an accuracy of 99% on the GPDS data from SVM classification.
本文重点介绍了一种离线签名验证与识别方法。研究了两种图像描述符，包括有向梯度金字塔直方图(PHOG)和文献中提出的方向特征。与以往提出的许多签名特征提取方法相比，PHOG在从手写签名图像中提取判别信息方面具有优势。强调了分类框架的重要性。在GPDS (Grupo de Procesado Digital de Senales)基准数据库中，多个分类器均获得了满意的性能。在所比较的分类器中，支持向量机显然更优越，对熟练伪造的错误拒绝率(FRR)为2.5%，错误接受率(FAR)为2%，这与同一数据集上最新发表的结果相比非常明显。这证实了所提方法的优越性。在此基础上，研究了基于SVM分类的GPDS数据离线签名识别的相关问题，准确率达到99%。
{"title":"Offline signature verification and identification by hybrid features and Support Vector Machine","authors":"Bailing Zhang","doi":"10.1504/IJAISC.2011.042717","DOIUrl":"https://doi.org/10.1504/IJAISC.2011.042717","url":null,"abstract":"This paper emphasised an approach for offline signature verification and identification. Two image descriptors are studied, including Pyramid Histogram of Oriented Gradients (PHOG), and a direction feature proposed in the literature. Compared with many previously proposed signature feature extraction approaches, PHOG has advantages in the extraction of discriminative information from handwriting signature images. The significance of classification framework is stressed. With the benchmarking database ||Grupo de Procesado Digital de Senales|| (GPDS), satisfactory performances were obtained from several classifiers. Among the classifiers compared, SVM is clearly superior, giving a False Rejection Rate (FRR) of 2.5% and a False Acceptance Rate (FAR) 2% for skillful forgery, which compares sharply with the latest published results on the same dataset. This substantiates the superiority of the proposed method. The related issue offline signature recognition is also investigated based on the same approach, with an accuracy of 99% on the GPDS data from SVM classification.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128202955","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}
Pub Date : 2011-09-01DOI: 10.1504/IJAISC.2011.042714
Fei Liu, J. Roddick
Some resolution strategies, such as SLD-resolution, are such that a derivation may be infinite even on a logic program that has a finite Herbrand universe. This paper introduces GOPT-resolution, a new deduction strategy for deriving solutions from a set of rules that improves on previous methods by preventing derivations that have infinite recursion. The paper outlines the process behind the development of GOPT-resolution based on PT-resolution. GOPT-resolution is then developed by distinguishing between goal-relevant and goal-irrelevant P-domains.
{"title":"GOPT Resolution","authors":"Fei Liu, J. Roddick","doi":"10.1504/IJAISC.2011.042714","DOIUrl":"https://doi.org/10.1504/IJAISC.2011.042714","url":null,"abstract":"Some resolution strategies, such as SLD-resolution, are such that a derivation may be infinite even on a logic program that has a finite Herbrand universe. This paper introduces GOPT-resolution, a new deduction strategy for deriving solutions from a set of rules that improves on previous methods by preventing derivations that have infinite recursion. The paper outlines the process behind the development of GOPT-resolution based on PT-resolution. GOPT-resolution is then developed by distinguishing between goal-relevant and goal-irrelevant P-domains.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123449047","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}
Pub Date : 2011-09-01DOI: 10.1504/IJAISC.2011.042710
G. Mota-Valtierra, L. Franco-Gasca, G. H. Ruiz
Industry has monitoring systems to determine the tool condition and to ensure quality. This paper presents an intelligent classification system which determines the status of cutters in a CNC milling machine. The tool states are detected through the analysis of the cutting forces drawn from the spindle motors currents. A wavelet transformation was used in order to compress the data and to optimise the classifier structure. Then a supervised SOM neural network is responsible for carrying out the classification of the signal. Achieving a reliability of 95%, the system is capable of detecting breakage and a worn cutter.
{"title":"Sensorless intelligent classifier of tool condition in a CNC milling machine using a SOM supervised neural network","authors":"G. Mota-Valtierra, L. Franco-Gasca, G. H. Ruiz","doi":"10.1504/IJAISC.2011.042710","DOIUrl":"https://doi.org/10.1504/IJAISC.2011.042710","url":null,"abstract":"Industry has monitoring systems to determine the tool condition and to ensure quality. This paper presents an intelligent classification system which determines the status of cutters in a CNC milling machine. The tool states are detected through the analysis of the cutting forces drawn from the spindle motors currents. A wavelet transformation was used in order to compress the data and to optimise the classifier structure. Then a supervised SOM neural network is responsible for carrying out the classification of the signal. Achieving a reliability of 95%, the system is capable of detecting breakage and a worn cutter.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116449402","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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