{"title":"Improved Lagrange Nonlinear Programming Neural Networks for Inequality Constraints","authors":"Yuancan Huang, Chuang Yu","doi":"10.1109/IJCNN.2007.4371088","DOIUrl":"https://doi.org/10.1109/IJCNN.2007.4371088","url":null,"abstract":"By redefining multiplier associated with inequality constraint as a positive definite function of the originally-defined multiplier, ui 2, i = 1, 2,..., m, say, the nonnegative constraints imposed on inequality constraints in Karush-Kuhn-Tucker necessary conditions are removed completely. Hence it is no longer necessary to convert inequality constraints into equality constraints by slack variables in order to reuse those results concerned only with equality constraints. Utilizing this technique, improved Lagrange nonlinear programming neural networks are devised, which handle inequality constraints directly without adding slack variables. Then the local stability of the proposed Lagrange neural networks is analyzed rigorously with Lyapunov's first approximation principle, and its convergence is discussed deeply with LaSalle's invariance principle. Finally, an illustrative example shows that the proposed neural networks can effectively solve the nonlinear programming problems","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126372077","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}
{"title":"Enhancement Filter for Computer-Aided Detection of Pulmonary Nodules on Thoracic CT images","authors":"Yang Yu, Hong Zhao","doi":"10.1109/ISDA.2006.253783","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253783","url":null,"abstract":"Computer-aided detection (CAD) schemes can assist radiologists in the early detection of lung cancer which is crucial to the chance for curative treatment. Characterizing the pulmonary nodules in the multislice X-ray computed tomography (CT) images is notoriously difficult. This is due to the fact that the anatomical structures such as blood vessels, bronchi, and alveoli are subject to partial volume effects. Furthermore, the nodules connected with other dense anatomical structures increases the detection difficulties. In this paper, we propose a multiscale enhancement filter to improve the sensitivity for nodule detection, which is based on the undecimated wavelet transform and the eigenvalues of Yu matrix in multiplanar slices. As a preprocessing step of CAD for nodule detection, our enhancement filter can simultaneously enhance blob-like objects and suppress line-like structures. Therefore, it would be useful for reducing the number of false positives. We applied our enhancement filter to synthesized images and real medical images to demonstrate that it works well on enhancing a specific shape and suppressing other shapes. Our approach proposed in this paper is generic and can be applied for the analysis of blob-like structures in various other applications","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127404485","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}
{"title":"A View-Based Toeplitz-Matrix-Supported System for Word Recognition without Segmentation","authors":"Marek Tabedzki, K. Saeed","doi":"10.1109/ISDA.2006.253784","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253784","url":null,"abstract":"In this paper, new modifications and experiments for word recognition and classification are presented. The algorithm is based on recognizing the whole words without separating them into letters. The whole word is treated and analyzed as an image. The method is based on the modification of a novel view-based word recognition algorithm - an approach that was successfully used by the authors' in previous works. This method shows how to recognize words without segmentation. The top and bottom views of the word are analyzed in order to create the feature vector. Then the feature vector is processed by the aid of Toeplitz matrices. The obtained series of Toeplitz matrix minimal eigenvalues are used for classification. The results are promising","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130786246","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}
{"title":"Decoupling Control for Electrode System in Electric Arc Furnace based on Neural Network Inverse Identification","authors":"Zhang Shao-de","doi":"10.1109/ISDA.2006.253815","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253815","url":null,"abstract":"RBF neural network based on nearest neighbor clustering algorithm is applied for three-phase electrode system in electric arc furnace. Real-time on-line decoupling of MIMO inverse system is realized, and transfers MIMO system with strong coupling into individual pseudo linear plant. On the base of these, the method dealing linear system can be used for the pseudo linear system. The simulation and experiments indicate that this strategy is suitable for engineering","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115230975","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}
{"title":"The Integrated Methodology of Rough Set Theory and Support Vector Machine for Credit Risk Assessment","authors":"Jian-guo Zhou, Zhaoming Wu, Chenguang Yang, Qi Zhao","doi":"10.1109/ISDA.2006.267","DOIUrl":"https://doi.org/10.1109/ISDA.2006.267","url":null,"abstract":"According to the current situation of the credit risk assessment in commercial banks, a hybrid intelligent system is applied to the study of credit risk assessment in commercial banks, combining rough set approach and support vector machine (SVM). The information table can be reduced, which showed that the number of evaluation criteria such as financial ratios and qualitative variables was reduced with no information loss through rough set approach. And then, the reduced information table is used to develop classification rules and train SVM. The rationality of hybrid system is using rules developed by rough sets and SVM. The former is for an object that matches any of the rules and the latter is for one that does not match any of them. The effectiveness of the methodology was verified by experiments comparing traditional discriminant analysis model and BP neural networks with our approach","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115439906","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}
{"title":"Decentralized Adaptive Controller Design for Uncertain Large-Scale Time-Delay Systems","authors":"Jian-Qiang Xu, Shu-Zhong Chen","doi":"10.1109/ISDA.2006.253827","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253827","url":null,"abstract":"The problem of decentralized robust control is considered for a class of uncertain large-scale time-delay systems in the presence of mismatched and matched uncertainties. The interconnections are assumed to be bounded by a linear function of delayed states with unknown gains. The upper bounds of the matching uncertainties and perturbations are also assumed to be unknown. The adaptation laws are proposed to estimate such unknown bounds, and by making use of the LMI method, a class of decentralized robust adaptive controllers is constructed. Based on the Lyapunov stability theory and Lyapunov-Krasovskii functional, it is shown that the state trajectories of the large-scale systems are uniformly asymptotically to zero. Finally, a numerical example is given to demonstrate the validity of the results","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123047061","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}
{"title":"Ontology-based Vegetable Supply Chain Knowledge Searching System","authors":"Jun Yue, Zhenbo Li, Zetian Fu","doi":"10.1109/ISDA.2006.211","DOIUrl":"https://doi.org/10.1109/ISDA.2006.211","url":null,"abstract":"Representing and organizing knowledge is important for a semantic knowledge searching system. To implement vegetable supply chain knowledge searching, we build three ontologies on the base of our investigation: the vegetable supply chain domain ontology, the user ontology and the knowledge content ontology. And meantimes, a metadata model is set up, we integrate these ontologies and metadata model together by setting up the relationships of these classes. Finally we formalize the metadata by RDF (resource description framework) and implement the searching system on the knowledge database of vegetable supply chain. Through the semantic searching, the users can get more suitable knowledge of vegetable supply chain","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"57 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121010465","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}
{"title":"Applying the Semisupervised Bayesian Approach to Classifier Design","authors":"Yiqing Kong, Shitong Wang","doi":"10.1109/ISDA.2006.106","DOIUrl":"https://doi.org/10.1109/ISDA.2006.106","url":null,"abstract":"This paper adopts a Bayesian approach to learn an optimal nonlinear classifier that is relevant to the classification task of semisupervised problems. The approach uses a prior weight to emphasize on the importance of class, which acts as a parameter of the likelihood function for both labeled and unlabeled data. We derive an expectation-maximization (EM) algorithm to compute maximum likelihood point estimate. Experimental results demonstrate appropriate classification accuracy on both synthetic and benchmark data sets","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127532583","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}
{"title":"Position Control of Linear Servo System Using Intelligent Feedback Controller","authors":"Dongmei Yu, Qingding Guo, Qing Hu","doi":"10.1109/ISDA.2006.253818","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253818","url":null,"abstract":"This paper presents a new position tracking control strategy that meets the position tracking performance and the closed loop robustness to external disturbance and model parameters variations without parameter identification. In order to achieve the desired input-output tracking and disturbance rejection performance independently, a two-degree-of-freedom (2DOF) internal model control (IMC) is introduced in controller structure. Furthermore, based on fuzzy logic, the parameter of the feedback controller is adjusted on-line to improve robustness. The simulation results on a direct-drive permanent magnet linear synchronous motor (PMLSM) show that proposed method is effective on improving system robustness","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125879243","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}
{"title":"A Multi-Agent Agile Scheduling System for Job-Shop Problem","authors":"Zhanjun Wang, Yanbo Liu","doi":"10.1109/ISDA.2006.253918","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253918","url":null,"abstract":"This paper proposes a multi-agent scheduling system for dynamic job-shop problem. The negotiation mechanism between agents controlling resources and tasks is discussed. First, a hybrid MAS framework is built to satisfy the requirements of the agile scheduling. Then an intelligent algorithm is designed to reason environment encountered and recommend adaptive scheduling algorithm for resource agents. And multi-objective function considering tardiness, waiting time and cost is designed for task agents as an evaluation criteria of resources' bids. The results obtained show the effective and good performance of this system in total flow time, total waiting time and makespan","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115222200","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}