2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)最新文献_第6页

Neural network based robust adaptive tracking control for the automomous underwater vehicle 基于神经网络的自主水下航行器鲁棒自适应跟踪控制

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI: 10.1109/ICACI.2016.7449854

Ye Tian, Tie-shan Li, Baobin Miao, W. Luo

引用次数: 0

Visualization and analysis of public social geodata to provide situational awareness 可视化和分析公共社会地理数据，提供态势感知

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI: 10.1109/ICACI.2016.7449805

A. Amirkhanyan, C. Meinel

引用次数: 6

Set-based particle swarm optimization for mapping and scheduling tasks on heterogeneous embedded systems 基于集合的粒子群算法在异构嵌入式系统任务映射和调度中的应用

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI: 10.1109/ICACI.2016.7449845

Xiao-Xiao Xu, Xiaomin Hu, Wei-neng Chen, Yun Li

{"title":"Set-based particle swarm optimization for mapping and scheduling tasks on heterogeneous embedded systems","authors":"Xiao-Xiao Xu, Xiaomin Hu, Wei-neng Chen, Yun Li","doi":"10.1109/ICACI.2016.7449845","DOIUrl":"https://doi.org/10.1109/ICACI.2016.7449845","url":null,"abstract":"Modern heterogeneous multiprocessor embedded platforms is important for the high volume markets that have strict performance. However, it presents many challenges that need to be addressed in order to be efficiently utilized for multitask applications. Since mapping and scheduling problems for multi processors belong to the classic of NP-Complete problems, common methods used to solve this kind of problem usually fail. In this paper, we present an algorithm based on the meta-heuristic optimization technique, set-based discrete particle swarm optimization (S-PSO), which efficiently solves scheduling and mapping problems on the target platform. This algorithm can simultaneously addressed the mapping and scheduling problems on a complex and heterogeneous MPSoC and it has better performance than other algorithms in dealing with large scale problems. This algorithm also reduces the execution time of the application by exploring various solutions for mapping and scheduling of tasks and communications. We compare our approach with other heuristics, Ant Colony Optimization (ACO), on the performance to reach the optimum value and on the potential to explore the target platform. The results show that our approach performs better than other heuristics.","PeriodicalId":211040,"journal":{"name":"2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133123582","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

An effective side information generation scheme for Wyner-Ziv video coding 一种有效的Wyner-Ziv视频编码侧信息生成方案

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI: 10.1109/ICACI.2016.7449842

Bodhisattva Dash, Suvendu Rup, A. Mohapatra, B. Majhi

{"title":"An effective side information generation scheme for Wyner-Ziv video coding","authors":"Bodhisattva Dash, Suvendu Rup, A. Mohapatra, B. Majhi","doi":"10.1109/ICACI.2016.7449842","DOIUrl":"https://doi.org/10.1109/ICACI.2016.7449842","url":null,"abstract":"Distributed Video Coding (DVC) is a video coding archetype that explores the source statistics at the decoder and hence reducing the encoder complexity. The Rate-Distortion (RD) performance of DVC strongly depends on the quality of the side information (SI) generation. So, efficient techniques to generate reliable SI are therefore essential to obtain a better quality of decoded video. In this paper, a SI generation technique based on radial basis function neural network (RBFNN) is proposed. RBF networks are widely used in various applications including function approximation and pattern recognition. Compared to other feed-forward neural networks, it has many advantages which makes it more suitable for nonlinear system modeling. The proposed model is trained and tested with different standard video sequences. The proposed scheme is merged with Transform Domain Wyner-Ziv (TDWZ) architecture and different experiments are performed to derive an overall conclusion. The overall experimental results demonstrate that the proposed technique produces an improved result in terms of Peak Signal to Noise Ratio (PSNR), bit rate, number of parity requests, decoding time complexity, etc. as compared to the existing state-of-art techniques.","PeriodicalId":211040,"journal":{"name":"2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114769824","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

Community detection using nonnegative matrix factorization with orthogonal constraint 基于正交约束的非负矩阵分解的群体检测

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI: 10.1109/ICACI.2016.7449802

Yaoyao Qin, Caiyan Jia, Yafang Li

引用次数: 3

Stock price manipulation detection using a computational neural network model 利用计算神经网络模型检测股价操纵行为

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI: 10.1109/ICACI.2016.7449848

Teema Leangarun, P. Tangamchit, S. Thajchayapong

{"title":"Stock price manipulation detection using a computational neural network model","authors":"Teema Leangarun, P. Tangamchit, S. Thajchayapong","doi":"10.1109/ICACI.2016.7449848","DOIUrl":"https://doi.org/10.1109/ICACI.2016.7449848","url":null,"abstract":"We investigated the characteristics of stock price manipulation. Two manipulation models were studied: pump-and-dump and spoof trading. Pump-and-dump is a procedure to buy a stock and push its price up. Then, the manipulator dumps all of the stock he holds to make a profit. Spoof trading is a procedure to trick other investors that a stock should be bought or sold at the manipulated price. We constructed mathematical models that use level 2 data for both procedures, and used them to generate a training set consisting of buy/sell orders within on order book of 10 depths. Order cancellations, which are important indicators for price manipulation, are also visible in our level 2 data. In this paper, we consider a challenging scenario where we attempt to use less-detailed level 1 data to detect manipulations even though using level 2 data is more accurate. We implemented feedforward neural network models that have level 1 data, containing less-detailed information (no information about order cancellation), but is more accessible to investors as input. The neural network model achieved 88.28% for detecting pump-and-dump but it failed to model spoof trading effectively.","PeriodicalId":211040,"journal":{"name":"2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133555898","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

Coordinative allocation model and method of equipment maintenance materiel 设备维修物资协调分配模型与方法

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI: 10.1109/ICACI.2016.7449798

Tiening Wang, Shuangshuang Yu, Ning Li, Shengliang Xu, Chao Yun, Qinqin Wang

引用次数: 0

Finite-time projective synchronization control of uncertain complex networks with brushless DC motor and Rikitake system 无刷直流电机和Rikitake系统不确定复杂网络的有限时间投影同步控制

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI: 10.1109/ICACI.2016.7449811

Meng Zhang, Min Han

{"title":"Finite-time projective synchronization control of uncertain complex networks with brushless DC motor and Rikitake system","authors":"Meng Zhang, Min Han","doi":"10.1109/ICACI.2016.7449811","DOIUrl":"https://doi.org/10.1109/ICACI.2016.7449811","url":null,"abstract":"The finite-time projective synchronization control of two uncertain complex networks with Brushless DC motor (BLDCM) and Rikitake system is investigated. Based on the finite-time stability theory and adaptive technique, a novel and useful finite-time synchronization control criteria is proposed. The effective synchronization controller and corresponding update laws are designed to guarantee projective synchronization control of the two uncertain complex networks in a given finite-time. Simultaneously, the unknown parameters of node dynamics are estimated successfully and the uncertain topological structure tend to the proper constants. Especially, the proposed approach can rapidly track the network topology changes well and the weight topological structure values are automatically adapted to the appropriate constants in the process of synchronization control. To validate the proposed method, introduced the Brushless DC motor (BLDCM) and Rikitake system with uncertainties as the nodes of the networks, and numerical simulations are given to illustrate the theoretical results.","PeriodicalId":211040,"journal":{"name":"2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116291900","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

Data mining approach for automatic discovering success factors relationship statements in full text articles 全文文章中成功因素关系语句自动发现的数据挖掘方法

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI: 10.1109/ICACI.2016.7449820

Worarat Krathu, P. Padungweang, Chakarida Nukoolkit

{"title":"Data mining approach for automatic discovering success factors relationship statements in full text articles","authors":"Worarat Krathu, P. Padungweang, Chakarida Nukoolkit","doi":"10.1109/ICACI.2016.7449820","DOIUrl":"https://doi.org/10.1109/ICACI.2016.7449820","url":null,"abstract":"In the context of Business-to-Business (B2B), an understanding of inter-organizational success factors and their impacts is crucial for effective strategic management. Several studies regarding those success factors and their influences have been conducted and published as articles. We aim at applying existing techniques, especially data mining, to automatically classify relevant sentences describing an influencing relationship between success factors. This paper presents the experiment method and results to find the optimal data mining workflow for our classification task. In particular, we apply several well-known data mining techniques based on different control factors. Then all discovered models are evaluated and compared to find the optimal data mining workflow. The main contributions include (i) the application of data mining for discovering success factors and their relationships, and (ii) the optimal workflow as a standardized flow for further similar classification tasks. The major challenge of this work is that there exists no mature corpus in this context, and hence our approach is implemented without a supporting corpus. The result shows that the models derived from the workflows that consider a section where a sentence is located perform better than the others in term of average performance. Furthermore, we found that the Support Vector Machine (SVM) performs better than other classifiers.","PeriodicalId":211040,"journal":{"name":"2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115833198","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

Feature extraction in hyperspectral imaging using adaptive feature selection approach 基于自适应特征选择方法的高光谱成像特征提取

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI: 10.1109/ICACI.2016.7449799

J. Rochac, N. Zhang

{"title":"Feature extraction in hyperspectral imaging using adaptive feature selection approach","authors":"J. Rochac, N. Zhang","doi":"10.1109/ICACI.2016.7449799","DOIUrl":"https://doi.org/10.1109/ICACI.2016.7449799","url":null,"abstract":"This paper presents the design and implementation of a new adaptive feature selection technique for spectral band selection prior to classification of remotely sensed hyperspectral images. This approach integrates spectral band selection and hyperspectral image classification in an adaptive fashion, with the ultimate goal of improving the analysis and interpretation of hyperspectral imaging. The four components in the proposed adaptive feature selection, including local gradient calculation, reference cluster determination, prototype classes building using a fuzzy classifier, and relevant bands selection are presented in detail. The hyperspectral image data set from the ROSIS (Reflective Optics System Imaging Spectrometer) were used as training and testing data. We tested the effect of the approach on different number of selected spectral bands. The classification accuracy for AFS was illustrated by the ROC curve. In addition, in order to compare the proposed method with other methods, we applied the proposed adaptive feature selection (AFS) approach and the principal component analysis (PCA) method to the GentleBoost classifier using different number of spectral bands after processing the ROSIS Pavia scene. The experimental results demonstrated that the classification accuracies obtained by the AFS method are higher than that of the PCA method. In addition, for each method, the higher the number of spectral bands, the higher the classification accuracy.","PeriodicalId":211040,"journal":{"name":"2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)","volume":"475 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116027005","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: 16