The digital products gradually permeate into realistic life with their advantages such as high-efficiency, multi-function and intelligence, and the design of digital Products has already broken away from the original concept of product design. Based on the feature of the design of digital Products, the specific expression method and characteristic of the language of digital mechanical product design are emphasized in this paper. The result of the study indicates that the expression of the multi-variant implication of Products can provide a new visual angle for knowing Products completely, and can also present a new method for innovational design of Products.
{"title":"Expression of Design Implication for the Products in the Digital Environment","authors":"Chen Xu","doi":"10.1109/ISCID.2009.186","DOIUrl":"https://doi.org/10.1109/ISCID.2009.186","url":null,"abstract":"The digital products gradually permeate into realistic life with their advantages such as high-efficiency, multi-function and intelligence, and the design of digital Products has already broken away from the original concept of product design. Based on the feature of the design of digital Products, the specific expression method and characteristic of the language of digital mechanical product design are emphasized in this paper. The result of the study indicates that the expression of the multi-variant implication of Products can provide a new visual angle for knowing Products completely, and can also present a new method for innovational design of Products.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114997489","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}
RVM enables sparse classification and regression functions to be obtained by linearly-weighting a small number of fixed basis functions from a large dictionary of potential candidates. TOA on RVM has O(M3) time and O(M2) space complexity, where M is the training set size. It is thus computationally infeasible on very large data sets. TFA was put forward to overcome this problem ,but it is not perfect to large scale problems. We propose CB-TFA based on TFA. CB-TFA decompose large datasets to data blocks, get the solution by chain iteration, taking TFA as basis algorithm, reduce the time complexity further more while keeping high accuracy and sparsity simultaneously. Regression experiments with synthetical large benchmark data set demonstrates CB-TFA yields state-of-the-art performance.
{"title":"CB-TFA to RVM on Large Scale Problems","authors":"Gang Li, Shu-Bao Xing, Hui-feng Xue","doi":"10.1109/ISCID.2009.98","DOIUrl":"https://doi.org/10.1109/ISCID.2009.98","url":null,"abstract":"RVM enables sparse classification and regression functions to be obtained by linearly-weighting a small number of fixed basis functions from a large dictionary of potential candidates. TOA on RVM has O(M3) time and O(M2) space complexity, where M is the training set size. It is thus computationally infeasible on very large data sets. TFA was put forward to overcome this problem ,but it is not perfect to large scale problems. We propose CB-TFA based on TFA. CB-TFA decompose large datasets to data blocks, get the solution by chain iteration, taking TFA as basis algorithm, reduce the time complexity further more while keeping high accuracy and sparsity simultaneously. Regression experiments with synthetical large benchmark data set demonstrates CB-TFA yields state-of-the-art performance.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134407374","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}
After a survey of existing methods, a fleet planning mixed integer programming model based on multimode investment is developed in accordance with route and transport demand forecast under the fluctuant market environment. This optimization model not only considers investment alternatives to fleet capacity expansion concerning building new ships, purchase or sale of second-hand ships, charter ships, but also takes into account many factors such as the economic status of the ships, ship deployment, the investment capacity of enterprise, etc., as well as reflects how much weight the decision makers have given to physical value of the fleet at the end of the research horizon. Lastly, effectiveness of the proposed model was demonstrated using a shipping enterprise as an example. Results indicate that, the model well meets the practical needs of the fleet planning decision-making and ship operation organizations, thus it can be applied to the fleet planning study on industrial transport or liner trunk transport.
{"title":"Modeling Fleet Planning Strategy Based on Multimode Investment","authors":"Qiuping Yang, Xinlian Xie, Weiwei Huo","doi":"10.1109/ISCID.2009.130","DOIUrl":"https://doi.org/10.1109/ISCID.2009.130","url":null,"abstract":"After a survey of existing methods, a fleet planning mixed integer programming model based on multimode investment is developed in accordance with route and transport demand forecast under the fluctuant market environment. This optimization model not only considers investment alternatives to fleet capacity expansion concerning building new ships, purchase or sale of second-hand ships, charter ships, but also takes into account many factors such as the economic status of the ships, ship deployment, the investment capacity of enterprise, etc., as well as reflects how much weight the decision makers have given to physical value of the fleet at the end of the research horizon. Lastly, effectiveness of the proposed model was demonstrated using a shipping enterprise as an example. Results indicate that, the model well meets the practical needs of the fleet planning decision-making and ship operation organizations, thus it can be applied to the fleet planning study on industrial transport or liner trunk transport.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128902613","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 this paper, a comparative study with three support vector machines (SVM) classifiers was carried out. The input images were first preprocessed to form the candidate text string regions. Next, Based on different features sets extracted by different methods, three SVM classifiers are used to analyze the textural properties of text and classify the text and no text strings in video frames. Then, a comparative evaluation of their performance is presented. The goal of the paper is to identify good feature selection for SVM in video text detecting task.
{"title":"A Comparative Study of Feature Selection for SVM in Video Text Detection","authors":"Zhen Wang, Zhiqiang Wei","doi":"10.1109/ISCID.2009.284","DOIUrl":"https://doi.org/10.1109/ISCID.2009.284","url":null,"abstract":"In this paper, a comparative study with three support vector machines (SVM) classifiers was carried out. The input images were first preprocessed to form the candidate text string regions. Next, Based on different features sets extracted by different methods, three SVM classifiers are used to analyze the textural properties of text and classify the text and no text strings in video frames. Then, a comparative evaluation of their performance is presented. The goal of the paper is to identify good feature selection for SVM in video text detecting task.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117205484","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}
Fit is an important standard of a consumer to evaluate an apparel product. Many developed nations have already begun the study on E-MTM (Electronic Made to Measure) system currently. The base and key of the MTM is the 3D body measurement system (BMS). In this paper, we choose the figure model of VRML format to extract sets of the intersection points of the figure model and given plains with the height defined as the characteristic sections height from the output of [TC]2 in ORD format, calculate the areas of figure characteristic sections and the ratio of the girth to area. The round or flatter type of figure can be judged by quantitative analysis for apparel personal design and manufacture.
{"title":"Study Apparel Made to Measure Based on 3D Body Scanner","authors":"Qiming Wang, Tianxiang Zhou, Weiyuan Zhang","doi":"10.1109/ISCID.2009.269","DOIUrl":"https://doi.org/10.1109/ISCID.2009.269","url":null,"abstract":"Fit is an important standard of a consumer to evaluate an apparel product. Many developed nations have already begun the study on E-MTM (Electronic Made to Measure) system currently. The base and key of the MTM is the 3D body measurement system (BMS). In this paper, we choose the figure model of VRML format to extract sets of the intersection points of the figure model and given plains with the height defined as the characteristic sections height from the output of [TC]2 in ORD format, calculate the areas of figure characteristic sections and the ratio of the girth to area. The round or flatter type of figure can be judged by quantitative analysis for apparel personal design and manufacture.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116015747","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}
Extreme learning machine (ELM) has shown to be extremely fast with better generalization performance. The basic idea of ELM algorithm is to randomly choose the parameters of hidden nodes and then use simple generalized inverse operation to solve for the output weights of the network. Such a procedure faces two problems. First, ELM tends to require more random hidden nodes than conventional tuning-based algorithms. Second, subjectivity is involved in choosing appropriate number of random hidden nodes. In this paper, we propose an enhanced-ELM(en-ELM) algorithm by applying the modified Gram-Schmidt (MGS) method to select hidden nodes in random hidden nodes pool. Furthermore, enhanced-ELM uses the Akaike's final prediction error (FPE) criterion to automatically determine the number of random hidden nodes. In comparison with conventional ELM learning method on several commonly used regressor benchmark problems, enhanced-ELM algorithm can achieve compact network with much faster response and satisfactory accuracy.
极限学习机(ELM)具有极快的学习速度和较好的泛化性能。ELM算法的基本思想是随机选择隐藏节点的参数，然后用简单的广义逆运算求解网络的输出权值。这样的程序面临两个问题。首先，与传统的基于调优的算法相比，ELM往往需要更多的随机隐藏节点。其次，选择适当数量的随机隐藏节点涉及主观性。本文采用改进的Gram-Schmidt (MGS)方法在随机隐藏节点池中选择隐藏节点，提出了一种增强的elm (en-ELM)算法。此外，增强elm使用赤池最终预测误差(Akaike’s final prediction error, FPE)准则自动确定随机隐藏节点的数量。在几种常用的回归量基准问题上，与传统的ELM学习方法相比，增强的ELM算法可以获得紧凑的网络，并且具有更快的响应速度和令人满意的精度。
{"title":"Modified Gram-Schmidt Algorithm for Extreme Learning Machine","authors":"Jianchuan Yin, Fang Dong, Nini Wang","doi":"10.1109/ISCID.2009.275","DOIUrl":"https://doi.org/10.1109/ISCID.2009.275","url":null,"abstract":"Extreme learning machine (ELM) has shown to be extremely fast with better generalization performance. The basic idea of ELM algorithm is to randomly choose the parameters of hidden nodes and then use simple generalized inverse operation to solve for the output weights of the network. Such a procedure faces two problems. First, ELM tends to require more random hidden nodes than conventional tuning-based algorithms. Second, subjectivity is involved in choosing appropriate number of random hidden nodes. In this paper, we propose an enhanced-ELM(en-ELM) algorithm by applying the modified Gram-Schmidt (MGS) method to select hidden nodes in random hidden nodes pool. Furthermore, enhanced-ELM uses the Akaike's final prediction error (FPE) criterion to automatically determine the number of random hidden nodes. In comparison with conventional ELM learning method on several commonly used regressor benchmark problems, enhanced-ELM algorithm can achieve compact network with much faster response and satisfactory accuracy.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129154874","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}
Based on the theories of Fuzzy Math and Analytic Hierarchy Process(AHP), combining the natural, social and economic characteristics of rock and soil filled dam and adequately considering different factors or indexes imposed on the safe operation of earthfill dam, the general safety assessment of earthfill dam through using multi-stratum fuzzy evaluation has been established. Furthermore, the safety assessment indexes, the theory of assessment, comprehensive weighting coefficient matrix and resolution methods are also established. From the practical measurement of rock and soil filled dam, multi-stratum fuzzy evaluation method which is used to assess the comprehensive safety is reasonable and practical.
{"title":"The Comprehensive Safety Assessment of Earthfill Dam Based on Multi-stratum Fuzzy Evaluation","authors":"Hui Peng, Yu-xin Huang","doi":"10.1109/ISCID.2009.61","DOIUrl":"https://doi.org/10.1109/ISCID.2009.61","url":null,"abstract":"Based on the theories of Fuzzy Math and Analytic Hierarchy Process(AHP), combining the natural, social and economic characteristics of rock and soil filled dam and adequately considering different factors or indexes imposed on the safe operation of earthfill dam, the general safety assessment of earthfill dam through using multi-stratum fuzzy evaluation has been established. Furthermore, the safety assessment indexes, the theory of assessment, comprehensive weighting coefficient matrix and resolution methods are also established. From the practical measurement of rock and soil filled dam, multi-stratum fuzzy evaluation method which is used to assess the comprehensive safety is reasonable and practical.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"174 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113984885","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}
Ensemble learning is considered as an important method to improve the accuracy of data mining and machine learning. On the base of the analysis of the basic concepts of ensemble learning, the design of ensemble learning model is divided into three stages: classifier construction, classifier integration and classification result integration, then the method of increasing prediction accuracy were discussed from three aspects: controlling classifier error, enhancing generalization ability and distinguishing acceptance-error in the application. Then, the influencing factors and the increasing methods of the three stages were studied through the instance experiments in WEKA, and we found it is of great significance to construct a reasonable integrated learning model.
{"title":"Analysis of Influencing Factors on Forecast Accuracy of Ensemble Learning","authors":"Fuliang Guo, Gang Zhou","doi":"10.1109/ISCID.2017.30","DOIUrl":"https://doi.org/10.1109/ISCID.2017.30","url":null,"abstract":"Ensemble learning is considered as an important method to improve the accuracy of data mining and machine learning. On the base of the analysis of the basic concepts of ensemble learning, the design of ensemble learning model is divided into three stages: classifier construction, classifier integration and classification result integration, then the method of increasing prediction accuracy were discussed from three aspects: controlling classifier error, enhancing generalization ability and distinguishing acceptance-error in the application. Then, the influencing factors and the increasing methods of the three stages were studied through the instance experiments in WEKA, and we found it is of great significance to construct a reasonable integrated learning model.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114970092","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}
To recognize the organizational structure of fabrics effectively, a fabric image segmentation method based on multi-scale Markov random field (MRF) was presented. Multi-scale MRF was applied to segment fabric images combined with edge information, which is extracted by the modulus maximum of wavelet transform. Experimental results show that the segmentation algorithm associated with edge information can reduce the computing time and most misclassifications. So, the approach is feasible and effective for fabric image segmentation.
{"title":"Multi-scale Markov Random Field Based Fabric Image Segmentation Associate with Edge Information","authors":"Ruilin Zhang, Yan Hu, W. Guo, Chenyan Zhang","doi":"10.1109/ISCID.2009.148","DOIUrl":"https://doi.org/10.1109/ISCID.2009.148","url":null,"abstract":"To recognize the organizational structure of fabrics effectively, a fabric image segmentation method based on multi-scale Markov random field (MRF) was presented. Multi-scale MRF was applied to segment fabric images combined with edge information, which is extracted by the modulus maximum of wavelet transform. Experimental results show that the segmentation algorithm associated with edge information can reduce the computing time and most misclassifications. So, the approach is feasible and effective for fabric image segmentation.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129863241","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 : 1900-01-01DOI: 10.1109/ISCID.2018.10147
Yong Wu, M. Liao
With the continuous application and operation of the software system for many years, the amount of data accumulated in the system database will be larger and larger, resulting in a slower and slower calculation of seemingly simple statistics such as sum and average, which seriously affects the stable operation and user experience of the system. According to pyramidal algorithm, this paper first define and use the optimal accumulative total edge to realize the process of rapid accumulation, and then put forward the granularity classification of the algorithm, positive cumulative, reverse the accumulate and mixed, and presents the automatic selection for statistical methods according to actual condition. Finally, the paper gives the application process and operation effect of the method, the results show that the granularity division of pyramidal algorithm provides the basis for the partition and decomposition of massive data.
{"title":"Granular Division and Calculation Process of Pyramidal Algorithm Based on Massive Data","authors":"Yong Wu, M. Liao","doi":"10.1109/ISCID.2018.10147","DOIUrl":"https://doi.org/10.1109/ISCID.2018.10147","url":null,"abstract":"With the continuous application and operation of the software system for many years, the amount of data accumulated in the system database will be larger and larger, resulting in a slower and slower calculation of seemingly simple statistics such as sum and average, which seriously affects the stable operation and user experience of the system. According to pyramidal algorithm, this paper first define and use the optimal accumulative total edge to realize the process of rapid accumulation, and then put forward the granularity classification of the algorithm, positive cumulative, reverse the accumulate and mixed, and presents the automatic selection for statistical methods according to actual condition. Finally, the paper gives the application process and operation effect of the method, the results show that the granularity division of pyramidal algorithm provides the basis for the partition and decomposition of massive data.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130339112","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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