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Int. J. Knowl. Eng. Soft Data Paradigms最新文献

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POFGEC: growing neural network of classifying potential function generators POFGEC:分类势函数生成器的生长神经网络
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2010-08-01 DOI: 10.1504/IJKESDP.2010.034679
N. Gueorguieva, I. Valova, G. Georgiev
{"title":"POFGEC: growing neural network of classifying potential function generators","authors":"N. Gueorguieva, I. Valova, G. Georgiev","doi":"10.1504/IJKESDP.2010.034679","DOIUrl":"https://doi.org/10.1504/IJKESDP.2010.034679","url":null,"abstract":"In this paper, we propose an architecture and learning algorithm for a growing neural network. Drawing inspiration from the idea of electrical potentials, we develop a classifier based on a set of synthesised potential fields over the domain of input space using symmetrical functions (kernels). We propose a multilayer, multiclass potential function generators classifier (POFGEC) utilising growing architecture and a training algorithm to sequentially add potential functions created by the training patterns, if the addition improves the NN classification performance. We also present a pruning algorithm to achieve compact architecture. POFGEC incorporates the electrical potentials concept in the two main neural net building blocks: potential function generators (PFGs) and potential function entities (PFEs), which perform a non-linear transformation of the input data and create the decision rules by constructing the cumulative potential functions and adjusting the weights. The implementation of the presented method with several datasets demonstrates its capabilities in generating classification solutions for datasets of various shapes independent from the number of predefined classes. We also offer substantial comparative analysis with other known approaches in order to fully illustrate the capabilities of the proposed method and its relation with other existing techniques.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127489574","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
An integrated intelligent computing method for the detection and interpretation of ECG based cardiac diseases 一种基于ECG的心脏疾病检测与解释的集成智能计算方法
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2010-08-01 DOI: 10.1504/IJKESDP.2010.034682
Babita Pandey, R. B. Mishra
{"title":"An integrated intelligent computing method for the detection and interpretation of ECG based cardiac diseases","authors":"Babita Pandey, R. B. Mishra","doi":"10.1504/IJKESDP.2010.034682","DOIUrl":"https://doi.org/10.1504/IJKESDP.2010.034682","url":null,"abstract":"Intelligent computing system and knowledge-based system have been widely used in the diagnosis and classification of ECG based diseases. Several detection methods of ECG parameters for a particular disease have also been reported in the literature. But little effort has been made by researchers to combine both. In this work, an integrated model of rule base system for generating cases and ANN methods for matching cases in the case base reasoning model for the interpretation and diagnosis of sinus disturbances (SD) is developed. The SD is hierarchically structured in terms of their physio-psycho parameters and ECG based parameters. Cumulative confidence factor (CCF) is computed at different nodes of hierarchy. The SD considered are sinus arrest, sinus bradycardia, sinus tachycardia and sinus arrhythmia. MIT/BIH ECG database is used in the simulation study. The basic objective of this work is to enhance the computational effort with certain level of efficiency and accuracy.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128186762","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: 12
Local subspace learning by extended fuzzy c-medoids clustering 扩展模糊c-介质聚类的局部子空间学习
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2010-08-01 DOI: 10.1504/IJKESDP.2010.034681
Naoki Haga, Katsuhiro Honda, A. Notsu, H. Ichihashi
{"title":"Local subspace learning by extended fuzzy c-medoids clustering","authors":"Naoki Haga, Katsuhiro Honda, A. Notsu, H. Ichihashi","doi":"10.1504/IJKESDP.2010.034681","DOIUrl":"https://doi.org/10.1504/IJKESDP.2010.034681","url":null,"abstract":"Linear fuzzy clustering is a technique for extracting linear-shape clusters, in which the fuzzy c-means (FCM)-like iterative procedure is performed with the prototypes of linear varieties, and is also regarded as a local subspace learning method. In fuzzy c-medoids (FCMdd), cluster prototypes are selected from data samples and clustering criteria are calculated by using only mutual distances among samples. Then, it is applicable to relational data clustering. This paper proposes an extended FCMdd approach for linear fuzzy clustering of relational data, which uses multiple representative objects (medoids) for representing prototypes. In the algorithm, new prototype is given by solving a combinatorial optimisation problem for searching medoids and the computational complexity is reduced by searching only from a subset of objects having large membership values. The information summarisation approach can be regarded as a multicluster-type multidimensional scaling for summarising data in multiple low-dimensional feature spaces.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122250648","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: 8
Element selection for intuitionistic fuzzy sets 直觉模糊集的元素选择
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2010-08-01 DOI: 10.1504/IJKESDP.2010.034680
V. Torra
{"title":"Element selection for intuitionistic fuzzy sets","authors":"V. Torra","doi":"10.1504/IJKESDP.2010.034680","DOIUrl":"https://doi.org/10.1504/IJKESDP.2010.034680","url":null,"abstract":"The need for element selection is a common need in decision making problems. While elements are evaluated using a numerical or total ordered scale, the selection can be done on the basis of the largest evaluation. Nevertheless, this approach cannot be applied when the scale is not totally ordered. This is the case when elements are evaluated using intuitionistic fuzzy sets or interval valued type 2 fuzzy sets. In this paper, we discuss element selection for this type of evaluations.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132604621","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
Neuro-fuzzy-combiner: an effective multiple classifier system 神经模糊组合器:一种有效的多分类器系统
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2010-08-01 DOI: 10.1504/IJKESDP.2010.034678
Ashish Ghosh, B. Uma Shankar, L. Bruzzone, S. Meher
{"title":"Neuro-fuzzy-combiner: an effective multiple classifier system","authors":"Ashish Ghosh, B. Uma Shankar, L. Bruzzone, S. Meher","doi":"10.1504/IJKESDP.2010.034678","DOIUrl":"https://doi.org/10.1504/IJKESDP.2010.034678","url":null,"abstract":"A neuro-fuzzy-combiner (NFC) is proposed to design an efficient multiple classifier system (MCS) with an aim to have an effective solution scheme for difficult classification problems. Although, a number of combiners exist in the literature, they do not provide consistently good performance on different datasets. In this scenario: 1) we propose an effective multiple classifier system (MCS) based on NFC that fuses the output of a set of fuzzy classifiers; 2) conduct an extensive experimental analysis to justify the effectiveness of the proposed NFC. In the proposed technique, we used a neural network to combine the output of a set of fuzzy classifiers using the principles of neuro-fuzzy hybridisation. The neural combiner adaptively learns its parameters depending on the input data, and thus the output is robust. Superiority of the proposed combiner has been demonstrated experimentally on five standard datasets and two remote sensing images. It performed consistently better than the existing combiners over all the considered datasets.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121552544","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: 26
Creating singing vocal expressions by means of interactive evolutionary computation 通过交互进化计算创造歌唱的声音表达
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2009-11-12 DOI: 10.1504/IJKESDP.2011.039877
Akio Watanabe, H. Iba
{"title":"Creating singing vocal expressions by means of interactive evolutionary computation","authors":"Akio Watanabe, H. Iba","doi":"10.1504/IJKESDP.2011.039877","DOIUrl":"https://doi.org/10.1504/IJKESDP.2011.039877","url":null,"abstract":"Today, research on singing by computers has attracted attention of researchers. VOCALOID is an application to realise that aim. By inputting lyrics and melody, users can make songs sung by the computer. In order to make the singing voice sound more human, users must control frequency curve very carefully. Compared with inputting lyrics or melody, this controlling presents heavy overhead for users. In this research, we propose a system for easily optimising frequency curves with Interactive Evolutionary Computation (IEC). We compared various frequency models by evaluating the convergence performance of GA to fit one of the frequency curves of real human singing, and found a suitable one for achieving our goal. And we made a questionnaire to compare previous interfaces and our IEC interface. From the results of this survey, we found our IEC interface can optimise frequency curve more easily than previous interfaces.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129125799","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
Basic study on effectiveness of tactile interface for warning presentation in driving environment 驾驶环境中触觉界面警示呈现有效性的基础研究
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2009-11-11 DOI: 10.1504/IJKESDP.2011.039881
A. Murata, Kouki Tanaka, M. Moriwaka
{"title":"Basic study on effectiveness of tactile interface for warning presentation in driving environment","authors":"A. Murata, Kouki Tanaka, M. Moriwaka","doi":"10.1504/IJKESDP.2011.039881","DOIUrl":"https://doi.org/10.1504/IJKESDP.2011.039881","url":null,"abstract":"The aim of this study was to get insight into the development of tactile interface for automobile warning system. In other words, it was investigated whether the important driving information in the right and left peripheral visual fields can be recognized faster using tactile warning system as compared with auditory warning system. The participants were required to simultaneously carry out a tracking task (main task), a switch pressing task such as selection of light-on function, and a judgment task of important information which randomly appeared to the right or left peripheral visual field. The tracking error, the number of lane deviation, the percentage correct of switch pressing, and the response time to right and left peripheral stimulus were measured. It was examined how age, the modality of alarm presentation (no alarm, auditory, and tactile), the addition of direction in alarm presentation, and the existence of disturbance sound, and the location of tactile sensor (steering or foot) affected the measures above. The young adults performed better than older adults. The response time was not affected by the modality of alarm presentation, and the disturbance sound. The\u0000addition of direction of alarm presentation affected the performance. The tactile sensor attached to the foot led to faster response than that attached to the steering wheel.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133796797","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: 15
Effects of state of eye movements before saccade on efficiency of response to stimulus - comparison of search efficiency between fixation and smooth pursuit states 扫视前眼动状态对刺激反应效率的影响——注视状态与平滑追求状态搜索效率的比较
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2009-11-10 DOI: 10.1504/IJKESDP.2011.039880
A. Murata, M. Moriwaka
{"title":"Effects of state of eye movements before saccade on efficiency of response to stimulus - comparison of search efficiency between fixation and smooth pursuit states","authors":"A. Murata, M. Moriwaka","doi":"10.1504/IJKESDP.2011.039880","DOIUrl":"https://doi.org/10.1504/IJKESDP.2011.039880","url":null,"abstract":"In this study, how the state of eye movement before saccade affected the response to a stimulus was explored. The state of eye movement before saccade was either smooth pursuit or fixation. The smooth pursuit was carried out both clockwise and counter-clockwise. Using an eye-tracking system, the eye movement during the experimental task was monitored. The response time to a stimulus was measured. On the basis of the eye movement data (coordinate), the eye movement velocity, the eye movement acceleration, and the latency of eye movement were obtained. When smooth pursuit was carried out before saccade, the response to a stimulus which appears as a result of saccade was faster. More concretely, the response time of smooth pursuit condition was faster than that of fixation condition. The latency of the smooth pursuit condition tended to be faster than that of the fixation condition. Some implications for the application of the results to the traffic safety or automotive ergonomics were given.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"8 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132339585","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
Borderline over-sampling for imbalanced data classification 不平衡数据分类的临界过采样
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2009-11-10 DOI: 10.1504/IJKESDP.2011.039875
Hien M. Nguyen, E. Cooper, K. Kamei
{"title":"Borderline over-sampling for imbalanced data classification","authors":"Hien M. Nguyen, E. Cooper, K. Kamei","doi":"10.1504/IJKESDP.2011.039875","DOIUrl":"https://doi.org/10.1504/IJKESDP.2011.039875","url":null,"abstract":"Traditional classification algorithms usually provide poor accuracy on the prediction of the minority class of imbalanced data sets. This paper proposes a new method for dealing with imbalanced data sets by over-sampling the borderline minority class instances. A Support Vector Machine (SVM) classifier is then trained to predict future instances. Compared with other over-sampling methods, the proposed method focuses only on the minority class instances residing along the decision boundary, due to the fact that this region is the most crucial for establishing the decision boundary. Furthermore, the artificial minority instances are generated in such a way that the regions of the minority class with fewer majority class instances would be expanded by extrapolation, otherwise the current boundary of the minority class would be consolidated by interpolation. Experimental results show that the proposed method achieves a better performance than other over-sampling methods.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126901460","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: 344
Clustering in the membership embedding space 隶属度嵌入空间中的聚类
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2009-10-01 DOI: 10.1504/IJKESDP.2009.028988
M. Filippone, F. Masulli, S. Rovetta
{"title":"Clustering in the membership embedding space","authors":"M. Filippone, F. Masulli, S. Rovetta","doi":"10.1504/IJKESDP.2009.028988","DOIUrl":"https://doi.org/10.1504/IJKESDP.2009.028988","url":null,"abstract":"In several applications of data mining to high-dimensional data, clustering techniques developed for low-to-moderate sized problems obtain unsatisfactory results. This is an aspect of the curse of dimensionality issue. A traditional approach is based on representing the data in a suitable similarity space instead of the original high-dimensional attribute space. In this paper, we propose a solution to this problem using the projection of data onto a so-called membership embedding space obtained by using the memberships of data points on fuzzy sets centred on some prototypes. This approach can increase the efficiency of the popular fuzzy C-means method in the presence of high-dimensional datasets, as we show in an experimental comparison. We also present a constructive method for prototypes selection based on simulated annealing that is viable for semi-supervised clustering problems.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128561310","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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