2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES)最新文献

From p-boxes to p-ellipsoids: Towards an optimal representation of imprecise probabilities 从p-盒到p-椭球:非精确概率的最佳表示

2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Pub Date : 2013-04-16 DOI: 10.1109/CIES.2013.6611742

K. Semenov, V. Kreinovich

引用次数: 0

An interactive genetic algorithm-based image sharpening system considering user's liking 考虑用户喜好的交互式遗传算法图像锐化系统

2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Pub Date : 2013-04-16 DOI: 10.1109/CIES.2013.6611734

Yoshiaki Ueda, Yohei Kuramoto, R. Kubota, N. Suetake, E. Uchino

{"title":"An interactive genetic algorithm-based image sharpening system considering user's liking","authors":"Yoshiaki Ueda, Yohei Kuramoto, R. Kubota, N. Suetake, E. Uchino","doi":"10.1109/CIES.2013.6611734","DOIUrl":"https://doi.org/10.1109/CIES.2013.6611734","url":null,"abstract":"Nowadays, digital images can be easily obtained, recorded and processed in accordance with the widespread use of digital cameras and personal computers. There is an image enhancement as one of most general image processing techniques. In the image enhancement, unsharp masking (UM) has been used widely because its algorithm is very simple and can produce good results. However, over-enhancement occurs in edge parts of the image. Additionally UM also is easy to generate artifacts such as jaggy and halo. To cope with these problems, the authors proposed the selective UM method based on the edge-preserved smoothing filter. However, the image quality obtained by our method depends on values of the enhancement parameters, and their optimal values vary according to user's liking. In this paper, we propose an image enhancement system considering the user's liking by using an interactive genetic algorithm (IGA). In the proposed system, the IGA optimizes the parameters of the image enhancement. Further, a new genetic operation is introduced in order to achieve the effective search in the IGA of the proposed system. Through the experiments using some images, the effectiveness of the proposed system is verified.","PeriodicalId":167449,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES)","volume":" 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132074558","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

Modified binary differential evolution for solving wind farm layout optimization problems 求解风电场布局优化问题的改进二元差分进化

2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Pub Date : 2013-04-16 DOI: 10.1109/CIES.2013.6611724

Dazhi Jiang, Chenfeng Peng, Zhun Fan, Yan Chen, Xinye Cai

引用次数: 14

Transitions-based system: A relevant use case 基于转换的系统:一个相关的用例

2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Pub Date : 2013-04-16 DOI: 10.1109/CIES.2013.6611749

T. Raimbault, David Genest, S. Loiseau

引用次数: 0

Research on hydropower station optimal scheduling considering ecological water demand 考虑生态需水量的水电站优化调度研究

2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Pub Date : 2013-04-16 DOI: 10.1109/CIES.2013.6611726

Wanliang Wang, Li Li, Xinli Xu, Xu Cheng, Yanwei Zhao

{"title":"Research on hydropower station optimal scheduling considering ecological water demand","authors":"Wanliang Wang, Li Li, Xinli Xu, Xu Cheng, Yanwei Zhao","doi":"10.1109/CIES.2013.6611726","DOIUrl":"https://doi.org/10.1109/CIES.2013.6611726","url":null,"abstract":"Considering that the standard particle swarm optimization has slow convergence speed and is easy to trap into local optimal solution, this paper proposed an improved algorithm with a dynamic neighborhood topology, where the connections between the particles are adjusted with a changing dynamical neighborhood structure of the particle. In the early stage of the algorithm, the impact of the optimal particle is weakened to maintain the diversity of the population and to prevent the algorithm from local optimum, then connections between particles are added to make the algorithm have more rapid convergence in the later stage. Focusing on hydropower optimal scheduling problems, we discussed relevant technologies, built the model of scheduling considering ecological water demand and studied the calculation of river Ecological Water Demand in the ecological operation of hydropower station. We combined ecological operation and generation scheduling taking maximum of power generation as the objective and taking into account constraints like ecological factors of the river, the balance of reservoir water, discharge volume restrictions, output restrictions etc., then we used an improved particle swarm algorithm to solve the optimization problem. The simulation scheduling results show that the algorithm has strong global search ability and rapid convergence speed, which can effectively solve such a multi-constrains, non-linearity problem in hydropower stations scheduling.","PeriodicalId":167449,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125149874","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: 6

Interactive particle swarm optimization for the architectural design of truss structures 基于交互粒子群算法的桁架结构设计

2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Pub Date : 2013-04-16 DOI: 10.1109/CIES.2013.6611723

J. Felkner, E. Chatzi, T. Kotnik

{"title":"Interactive particle swarm optimization for the architectural design of truss structures","authors":"J. Felkner, E. Chatzi, T. Kotnik","doi":"10.1109/CIES.2013.6611723","DOIUrl":"https://doi.org/10.1109/CIES.2013.6611723","url":null,"abstract":"This paper presents an interactive framework for the design of truss structures with aesthetic criteria. The truss chords are described using NURBS, a tool widely used in computer aided design (CAD) programs to describe free-form geometry. This allows for a convenient interface between the optimization scheme, a particle swarm optimizer, and the user. Driven from the fact that aesthetic design goals are not easily quantifiable, key elements are introduced and implemented herein towards an interactive framework for algorithmic design of truss structures. Within this framework, the user can visually assess interesting solutions, save them for later assessment, actively drive the optimization towards individual aims, re-initialize the optimization with a set of available solutions, or restart the design process. A criterion is introduced as a means of quantifying subjective goals, expressing the similarity of the shape of candidate solutions with respect to reference designs. The framework is tested on a benchmark case and then applied to the design of a truss tower. The effectiveness of the similarity criteria, as well as the ability of the user to drive the process towards specific design goals is demonstrated.","PeriodicalId":167449,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125167954","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: 18

Augmenting simulations with measurements 用测量增强模拟

2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Pub Date : 2013-04-16 DOI: 10.1109/CIES.2013.6611747

D. Vernay, B. Raphael, I. Smith

引用次数: 0

A hybrid evolutionary algorithm for OFDM resource allocation OFDM资源分配的混合进化算法

2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Pub Date : 2013-04-16 DOI: 10.1109/CIES.2013.6611727

Hai-Lin Liu, Qiang Wang

引用次数: 4

Computational intelligence-based identification of maximally sustainable materials: The case of liquid containers 基于计算智能的最大可持续材料识别:以液体容器为例

2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Pub Date : 2013-04-16 DOI: 10.1109/CIES.2013.6611736

Tatiana Tambouratzis, D. Karalekas, N. Moustakas

{"title":"Computational intelligence-based identification of maximally sustainable materials: The case of liquid containers","authors":"Tatiana Tambouratzis, D. Karalekas, N. Moustakas","doi":"10.1109/CIES.2013.6611736","DOIUrl":"https://doi.org/10.1109/CIES.2013.6611736","url":null,"abstract":"A novel computational intelligence methodology is proposed for identifying the properties of maximally sustainable materials for any given application; identification is based on the known properties of existing candidate materials. Once the correlation surface between material properties and environmental impact values of the candidate materials is created via a general regression artificial neural network, genetic algorithms are used for accurately as well as efficiently determining the minimum/a of the correlation surface, thus uncovering the properties of the maximally sustainable material(s). A demonstration is given for a simplified type of material selection concerning maximally sustainable liquid containers. The proposed methodology is compared to and found more accurate than classic interpolation techniques; additionally, sensitivity and multi-criteria analyses confirm stability of the methodology under variations in both the material property values of the known materials and in the relative importance of the input properties. It is important that this methodology can be directly applied to a variety of material selection tasks by choosing the input properties of interest as well as the desired material selection criteria.","PeriodicalId":167449,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128564037","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

A multiobjective particle swarm optimization algorithm for load scheduling in electric smelting furnaces 电炉负荷调度的多目标粒子群优化算法

2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Pub Date : 2013-04-16 DOI: 10.1109/CIES.2013.6611748

W. Kong, Jinliang Ding, T. Chai, Xiuping Zheng, Shengxiang Yang

{"title":"A multiobjective particle swarm optimization algorithm for load scheduling in electric smelting furnaces","authors":"W. Kong, Jinliang Ding, T. Chai, Xiuping Zheng, Shengxiang Yang","doi":"10.1109/CIES.2013.6611748","DOIUrl":"https://doi.org/10.1109/CIES.2013.6611748","url":null,"abstract":"Electric smelting furnaces, applied in the smelting process of infusible mineral, are highly energy-intensive. In China, they waste a huge amount of electric energy, but yield a small quantity of valuable metals due to the lack of optimized load scheduling strategies. In this paper, we design a multiobjective load scheduling method to minimize the electricity cost and maximize the production output and product quality. Firstly a load scheduling model is developed based on a least square support vector machine, which is a robust empirical model with simple formulation and low sensitivity to external disturbance. We utilize a modified multiobjective particle swarm optimization algorithm to solve the optimization model. The proposed algorithm adopts a supervised population initialization that reuses the past optimal solutions and digs out new candidate solutions to guide the current optimization. An elaborate constraint-handing strategy is devised, which repairs the infeasible solutions that violate the maximum demand constraint and reserve the ones that violate one production constraint but performing excellently on the other production targets. The case study on a typical magnesia-smelting plant shows that the proposed multi-objective load scheduling model and algorithm can achieve an increase of about 14.5% in the production output, an improvement of about 0.46% of the magnesia in the product, and a slight saving in electricity cost.","PeriodicalId":167449,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116021769","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