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Int. J. Artif. Intell. Soft Comput.最新文献

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Studies on intrinsic summary evaluation 内在总结性评价研究
Int. J. Artif. Intell. Soft Comput. Pub Date : 2010-04-01 DOI: 10.1504/IJAISC.2010.032513
S. Hariharan, R. Srinivasan
{"title":"Studies on intrinsic summary evaluation","authors":"S. Hariharan, R. Srinivasan","doi":"10.1504/IJAISC.2010.032513","DOIUrl":"https://doi.org/10.1504/IJAISC.2010.032513","url":null,"abstract":"Summary evaluation has gained importance in the research community and seems to be a quite challenging task. Most of the work till date focus on summary generation, while this paper focus on intrinsic summary evaluation. Studies made for preparing the 'Gold Standard' reference summary present some of the key issues in preparing a reference summary. Spearman, Kendall's W, and Kendall's rank correlation coefficients have been used for measuring inter-judge rank correlation. Existing drawbacks in Precision-Recall based evaluation and utility-based evaluation schemes were analysed. A new measure, called 'Effectiveness', to measure the system performance at given compression rate has been introduced.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129213416","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}
引用次数: 7
Incorporating trust into the BDI architecture 将信任整合到BDI体系结构中
Int. J. Artif. Intell. Soft Comput. Pub Date : 2010-02-01 DOI: 10.1504/IJAISC.2010.038641
T. Taibi
{"title":"Incorporating trust into the BDI architecture","authors":"T. Taibi","doi":"10.1504/IJAISC.2010.038641","DOIUrl":"https://doi.org/10.1504/IJAISC.2010.038641","url":null,"abstract":"Trust is becoming a major issue in Multi-Agent Systems (MAS), in which agents need to delegate some tasks to others. Trust can be defined as the degree of confidence in an agent's prediction of another agent's future behaviour. In the context of the BDI model, trust can be defined as the beliefs that one agent has of another's beliefs, desires, intentions and capabilities. This paper first presents our own version of BDI interpreter. Then, the above vision of trust is incorporated into the BDI interpreter in order to help an agent in the decision process before delegating tasks to other agents.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124586115","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}
引用次数: 4
An efficient classifier design integrating Rough Set and Dempster-Shafer Theory 结合粗糙集理论和Dempster-Shafer理论的分类器设计
Int. J. Artif. Intell. Soft Comput. Pub Date : 2010-02-01 DOI: 10.1504/IJAISC.2010.038643
A. Das, J. Sil
{"title":"An efficient classifier design integrating Rough Set and Dempster-Shafer Theory","authors":"A. Das, J. Sil","doi":"10.1504/IJAISC.2010.038643","DOIUrl":"https://doi.org/10.1504/IJAISC.2010.038643","url":null,"abstract":"An integrated approach of knowledge discovery has been proposed in the paper using Rough Set Theory (RST) and Dempster-Shafer's (D-S) theory where high dimensional data is reduced in two folds. Firstly, unimportant attributes are eliminated using RST generating minimal subset of attributes, called reducts. Considering each core attribute as root of a decision tree, classification rules are built and grouped based on some similarity measure. Representative of each group constitute the new rule set and thus rules has been reduced while important information are retained. D-S theory ensembles the rules from which a classifier with highest accuracy has been selected.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114137569","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}
引用次数: 1
Performance analysis of a proposed smoothing algorithm for isolated handwritten characters 一种孤立手写字符平滑算法的性能分析
Int. J. Artif. Intell. Soft Comput. Pub Date : 2010-02-01 DOI: 10.1504/IJAISC.2010.038638
M. F. Zafar, D. Mohamad, R. Othman
{"title":"Performance analysis of a proposed smoothing algorithm for isolated handwritten characters","authors":"M. F. Zafar, D. Mohamad, R. Othman","doi":"10.1504/IJAISC.2010.038638","DOIUrl":"https://doi.org/10.1504/IJAISC.2010.038638","url":null,"abstract":"This paper describes an online isolated character recognition system using advanced techniques of pattern smoothing and Direction Feature (DF) extraction. The composition of direction elements and their smoothing are directly performed on online trajectory, and therefore, are computationally efficient. We compare recognition performance when DFs are formulated using Smoothed Direction Vectors (SDV) and Unsmoothed Direction Vectors (UDV). In experiments, direction features from original pattern yielded inferior performance, whereas primitive sub-character direction features using smoothed direction-encoded vectors made significant difference. Recognition rates were improved by about 7% and 5% using SDV when compared with UDV and smoothed with Moving Average (MA) technique, respectively.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125238077","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}
引用次数: 0
Implementation of a novel LVQ neural network architecture on FPGA 一种新型LVQ神经网络结构在FPGA上的实现
Int. J. Artif. Intell. Soft Comput. Pub Date : 2010-02-01 DOI: 10.1504/IJAISC.2010.038635
Najoua Chalbi, K. Khalifa, Mohamed Boubaker, M. Hedi
{"title":"Implementation of a novel LVQ neural network architecture on FPGA","authors":"Najoua Chalbi, K. Khalifa, Mohamed Boubaker, M. Hedi","doi":"10.1504/IJAISC.2010.038635","DOIUrl":"https://doi.org/10.1504/IJAISC.2010.038635","url":null,"abstract":"The current study presents the hard implementation methodology of a Learning Vector Quantization (LVQ) neural network on a Field Programmable Gate Array (FPGA) circuit specially suited for fast output applications. The implementation methodology is based on a mixed parallel sequential approach with the use of the L2 norm (Euclidian distance) to measure the distance between the reference vector and the prototype vector. The adopted architecture has been implemented on a device XCV1000 (FPGA Xilinx) and the given results have shown good performances in time, surface and consumption.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124272970","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}
引用次数: 2
Optimal feature retrieval for classification of non-stationary Power Quality disturbances 非平稳电能质量扰动分类的最优特征检索
Int. J. Artif. Intell. Soft Comput. Pub Date : 2010-02-01 DOI: 10.1504/IJAISC.2010.038640
V. Pandi, S. Sinha, A. Mohapatra, B. K. Panigrahi, Swagatam Das
{"title":"Optimal feature retrieval for classification of non-stationary Power Quality disturbances","authors":"V. Pandi, S. Sinha, A. Mohapatra, B. K. Panigrahi, Swagatam Das","doi":"10.1504/IJAISC.2010.038640","DOIUrl":"https://doi.org/10.1504/IJAISC.2010.038640","url":null,"abstract":"Since last few decades, Power Quality (PQ) issues has drawn the attention of both the utilities and the customers. This paper presents one of the most advanced signal-processing techniques i.e., Wavelet Transform (WT) to extract some of the important useful features of the non-stationary PQ signal. The features are then used to classify the nature of the PQ disturbance. The feature dimension is further reduced by selecting the optimal set of features using Genetic Algorithm (GA) to achieve a higher classification accuracy. The optimal features obtained using GA are used to train a Support Vector Machine (SVM) classifier for automatic classification of the Power Quality (PQ) disturbances. Nine types of PQ disturbances are considered for the classification purpose. The simulation results show that the combination of WT and SVM can effectively classify different PQ disturbances.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"1991 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131116779","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}
引用次数: 0
High performance speed tracking of induction motor drives using an adaptive fuzzy-neural network control 基于自适应模糊神经网络控制的异步电机高速跟踪
Int. J. Artif. Intell. Soft Comput. Pub Date : 2010-02-01 DOI: 10.1504/IJAISC.2010.038642
M. Zerikat, S. Chekroun
{"title":"High performance speed tracking of induction motor drives using an adaptive fuzzy-neural network control","authors":"M. Zerikat, S. Chekroun","doi":"10.1504/IJAISC.2010.038642","DOIUrl":"https://doi.org/10.1504/IJAISC.2010.038642","url":null,"abstract":"This paper relates an adaptive speed control of hybrid fuzzy-neural network for high-performance induction motor drives. The speed control performance of induction motors is affected by parameter variations and non-linearities in the induction motor. The aim of the proposed control scheme is to improve the performance and robustness of the induction motor drives under non-linear loads and parameter variations. Both the design of the fuzzy controller and its integration with neural networks in a global control system are discussed. The simulation results showed excellent tracking performance of the proposed control system, and have convincingly demonstrated the usefulness of the hybrid fuzzy-neural controller in high-performance drives with uncertainty.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134052369","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}
引用次数: 1
The role of neuro-fuzzy modelling as a greening technique, in improving the performance of vehicular spark ignition engine 神经模糊建模作为一种绿色技术，在提高车用火花点火发动机性能中的作用
Int. J. Artif. Intell. Soft Comput. Pub Date : 2010-02-01 DOI: 10.1504/IJAISC.2010.038639
M. Amer, Y. Najjar
{"title":"The role of neuro-fuzzy modelling as a greening technique, in improving the performance of vehicular spark ignition engine","authors":"M. Amer, Y. Najjar","doi":"10.1504/IJAISC.2010.038639","DOIUrl":"https://doi.org/10.1504/IJAISC.2010.038639","url":null,"abstract":"The spark ignition engine, by far, is the largest source of motive power in the world. Therefore, continuous endeavours to improve its performance are needed to save in fuel consumption and reduce cost. The main goal of this paper is to develop a neuro-fuzzy model for fuel Injection Time (IT) in order to design a neuro-fuzzy controller for improving the performance of the spark ignition engine. The obtained results showed that the developed neuro-fuzzy model is capable of predicting the fuel IT with a mean squared error less than 0.0072. Furthermore, the power produced by the neuro-fuzzy controller has higher values of about 15-73% than the power produced by the PID controller used in the basic engine. The BSFC is reduced by about 2-5% compared to the PID controller.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125626888","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}
引用次数: 3
Hybrid approach for pole assignment using LQR technique and Ant System metaheuristic 基于LQR技术和蚂蚁系统元启发式的混合极点配置方法
Int. J. Artif. Intell. Soft Comput. Pub Date : 2009-07-01 DOI: 10.1504/IJAISC.2009.027292
H. Liouane, A. Douik, H. Messaoud
{"title":"Hybrid approach for pole assignment using LQR technique and Ant System metaheuristic","authors":"H. Liouane, A. Douik, H. Messaoud","doi":"10.1504/IJAISC.2009.027292","DOIUrl":"https://doi.org/10.1504/IJAISC.2009.027292","url":null,"abstract":"We present in this paper a new metaheuristic using Ant System metaheuristic to search an optimal command law in LQR sense that gives for a feedback system a given values by pole assignment. In fact, these hybrid techniques of conventional and non conventional methods present a good compromise between the simplicity of use and the quality of proposed solutions in a reasonable computing time. The results obtained by using this technique show its efficiency in the proposed problem and can be considered as a competitive method for those issued from a complicate mathematic formulation.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123732093","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}
引用次数: 2
Non-linear dynamic system identification using Cascaded Functional Link Artificial Neural Network 非线性动态系统的级联函数链人工神经网络辨识
Int. J. Artif. Intell. Soft Comput. Pub Date : 2009-07-01 DOI: 10.1504/IJAISC.2009.027293
B. Majhi, G. Panda
{"title":"Non-linear dynamic system identification using Cascaded Functional Link Artificial Neural Network","authors":"B. Majhi, G. Panda","doi":"10.1504/IJAISC.2009.027293","DOIUrl":"https://doi.org/10.1504/IJAISC.2009.027293","url":null,"abstract":"The Multilayer Artificial Neural Network (MLANN) has been employed for identification of non-linear dynamic systems. However, this scheme offers high computational complexity and yields poor identification performance particularly for non-linear dynamic systems. In this paper, we introduce a new structure known as Cascaded Functional Link Artificial Neural Network (CFLANN), derive an appropriate learning algorithm and use it for identification task. Extensive simulation study reveals that the proposed approach outperforms the existing MLANN-based method both in terms of computational complexity and response matching.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124544037","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}
引用次数: 3
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