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4th International Workshop on Advanced Computational Intelligence, IWACI 2011

作者： Chen, Chen Chen, Xueguang Liu, Hong Institute of Systems Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Lab. for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781612843735

Based on the current development of Model Driven Architecture (MDA) in Enterprise Information System (EIS), the paper proposes a DMDA, a new development architecture to improve EIS development speed and quality. The basic idea of the DMDA is to take advantage of formal description, decomposition and re-use on EIS development process to let computer understand development demands of developers and then consequently generate some business models having nothing to do with specific technical realization, combine with specific technical basic platform to finally generate the EIS meeting actual demands based on data model. The practice proves the architecture is capable of simplifying EIS development difficulty, expediting application and development speed, improve development quality and achieve the rapid development purpose. © 2011 IEEE.

关键词： Software design

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Asynchronous extended spiking neural P systems with astrocytes

Asynchronous extended spiking neural P systems with astrocyt...

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12th International Conference on Membrane Computing, CMC 2011

作者： Pan, Linqiang Wang, Jun Hoogeboom, Hendrik Jan Image Processing and Intelligent Control Key Laboratory of Education Ministry Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China Leiden Institute of Advanced Computer Science Universiteit Leiden Niels Bohrweg 1 2333 CA Leiden Netherlands

ISBN: (纸本)9783642280238

A variant of spiking neural P systems was recently investigated by the authors, using astrocytes that have excitatory and inhibitory influence on synapses. In this work, we consider this system in the non-synchronized (i.e., asynchronous) mode: in any step, when a neuron is enabled, it is not obligatorily fired, making a global clock dispensable. It is proved that asynchronous spiking neural P systems with astrocytes are universal (when using extended rules). The construction is uniform in the sense that the form of the modules used is independent of the simulated register machine. © 2012 Springer-Verlag.

关键词： Artificial intelligence

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Graph based co-training algorithm for web page classification

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2009年第10期37卷 2173-2180+2219页

作者： Hou, Cui-Qin Jiao, Li-Cheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an Shaanxi 710071 China

This paper proposes a novel inductive semi-supervised algorithm for web page classification named GCo-training, exploiting texts in web pages and hyperlinks among them. GCo-training iteratively trains two classifiers-a graph-based semi-supervised classifier based on hyperlinks among web pages and a Bayes classifier based on texts in web pages, under the framework of Co-training. On the one hand, the graph-based semi-supervised classifier obtains high accuracy based on a small set of labeled examples through exploiting links among web pages and can augment labeled examples for the Bayes classifier. On the other hand, the Bayes classifier can also provide labeled example for the graph-based classifier after it learning on labeled set augmented by the graph-based classifier. Therefore, the two classifiers help each other and improve their respective performance during the process of training. Finally, the Bayes classifier can classify a large number of unseen examples. We test GCo-training algorithm, Co-training algorithm based on words occurring on web pages and words occurring in hyperlinks and Bayes algorithm based on EM on the Web&KB dataset. Experimental results show GCo-training performs much better than the other algorithms.

关键词： Websites

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Multi-stage hybrid multiobjective evolutionary algorithm for multi-type vehicle routing problem with simultaneous pickup and delivery and time windows

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Computers & Industrial Engineering 2025年

作者： Wenqiang Zhang Shun Li Miaolei Deng Yashuang Mu Peng Li Key Laboratory of Grain Information Processing and Control (Henan University of Technology) Ministry of Education China Henan Key Laboratory of Grain Storage Information Intelligent Perception and Decision Making Henan University of Technology China School of Artificial Intelligence and Big Data Henan University of Technology China College of Information Science and Engineering Henan University of Technology China Institute for Complexity Science Henan University of Technology China

The vehicle routing problem (VRP) is a fundamental and extensively studied problem in logistics and transportation. Despite its significance, real-world applications often require more complex variants to address specific operational constraints and objectives. To address these limitations, this paper introduces the multi-type vehicle routing problem with simultaneous pickup and delivery and time windows (MTVRPSPDTW). Although hybrid multiobjective algorithms have been successful in combination optimization problems in recent years, it is still challenging to improve the performance of the algorithms by combining them with different timing. We propose a multi-stage hybrid evolutionary multi-objective optimization with a multi-region sampling strategy (MS-HEMO-MRSS) to optimize both vehicle number and wait time of MTVRPSPDTW. The algorithm integrates a three-stage hybrid approach, combining a global search using the multi-region sampling strategy (MRSS) with a local search based on routing sequence differential evolution (RSDE). The initial stage employs MRSS to quickly position the population near the Pareto front from various directions. The second stage utilizes RSDE to accelerate convergence towards central and edge areas of the Pareto front. In the final stage, individuals on Pareto front are selected and RSDE is used again to guide them towards the edge regions to enhance distribution performance. Specialized encoding, decoding techniques, and genetic operators tailored for two vectors are introduced to optimize MTVRPSPDTW. Comparative experiments with traditional multiobjective evolutionary algorithms demonstrate significant convergence and notable distribution performances, highlighting the benefits of employing different optimization strategies at different evolutionary stages.

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Knowledge-Based Scene Text Recognition for Industrial Applications

Knowledge-Based Scene Text Recognition for Industrial Applic...

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Deng, Guowei Tu, Jingzheng Chen, Cailian He, Jianping Le, Xinyi Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China 200240 Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai China 200240

ISBN: (纸本)9781728119489

Scene text recognition (STR) methods combined with semantic information have made great progress to recognize texts in natural scenes, most of which are daily words. However, research on mining semantic information in industrial texts attracts less attention. Since industrial texts follow a different semantic pattern defined by industry standards, it challenges many existing methods to conduct accurate semantic reasoning. In this paper, we abstract the industry standards into two aspects of prior knowledge: the grouping property and the prior lexicon. Correspondingly, a knowledge-based language model is proposed with several group-wise correlation modules and a lexicon-based reasoning module to learn semantic rules from both data and the prior knowledge. Besides, we transfer the prior knowledge into data by generating synthetic pure text datasets according to the industry standards' rules, which introduces more prior knowledge to the language model. Furthermore, a novel STR framework is presented by combining the knowledge-based language model and an attention-based vision model. For evaluation, two industrial text datasets called CIN and SB are collected from real-world industrial field surveillance. Experiments indicate that our method's word-level accuracy outperforms state-of-the-art methods with 15% and 10.61% on CIN and SB datasets respectively. © 2022 IEEE.

关键词： Knowledge based systems

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Heterogeneous belief formation method based on BP neural network 2

Heterogeneous belief formation method based on BP neural net...

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2nd International Conference on Electronic Information Technology and Computer Engineering, EITCE 2018

作者： Zhuang, Yifan Wang, Hongwei Chen, Xi School of Automation Huazhong University of Science and Technology Wuhan430074 China School of Management Huazhong University of Science and Technology Wuhan430074 China Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Wuhan430074 China

The BDI model has always been the focus of subject modeling research, which includes three kinds of thinking states of the rational subject: Belief, Desire and Intention. Belief is the cognition of agent to the world;it is a collection of environmental information, other agent information, and its own information that the agent has;and it is also the basis of the agent's thinking activity. Due to differences in the individual's living environment and experience, the formation of heterogeneous beliefs is an important issue in the BDI model study. This article divides individual belief set into two parts: knowledge belief and achievable belief. This article proposes an overall framework for the formation of individual heterogeneity beliefs: First, the individual's knowledge experience is modeled, and the empirical knowledge is structured and quantified into binary propositions;then the BP neural network learn and memory propositions of different combinations to form heterogeneous beliefs. Experiments show that this method can simulate the heterogeneity of individual beliefs caused by the individual's own experience, and can realize the belief generation mechanism of gradual information flow, limited attention and heterogeneous priors. © The Authors, published by EDP Sciences, 2018.

关键词： Neural networks

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DNA Strand Displacement Based on Nicking Enzyme for DNA Logic Circuits 1

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13th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2018

作者： Wang, Gaiying Wang, Zhiyu Yan, Xiaoshan Liu, Xiangrong School of Information Science and Technology Xiamen University XiamenFujian361005 China Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China

ISBN: (数字)9789811328268

ISBN: (纸本)9789811328251

DNA strand displacement is widely used in the construction of DNA molecule computational models. In this work, nicking enzyme is used as the input of the logic calculation model for it can cut one strand of a double-stranded DNA at a specific recognition nucleotide sequences known as a restriction site. Based on this, a variety of logic gates are designed and implemented, and a multi-person voting circuit is constructed. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Enzymes

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Interdependency analysis of infrastructures

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6th International Symposium on Neural Networks, ISNN 2009

作者： Mao, Zijun Hong, Liu Fei, Qi Ouyang, Ming Institute of System Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Lab. for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)3642015123

Electric power, potable water, telecommunications, natural gas, and transportation are examples of critical infrastructures, the intrinsic feature of which are suitable for network analysis. This paper proposes a method framework based on the complex network to explore the interdependency of these infrastructures. We describe the topological characterization of two interdependent small-sized real networks, based on which the interdependent model is devised. We define the interdependent factor to characterize the direct interdependency of two infrastructures, and also its fluctuation in the situations of random removal and targeted removal on the electric and water infrastructures is studied. Furthermore we propose a matrix M to reflect all direct and indirect interactions among infrastructures, which also makes contributions to the understanding of infrastructures catastrophes. © 2009 Springer Berlin Heidelberg.

关键词： Complex networks

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Automatic Recognition of Whale and Dolphin Whistles Based on Visual Feature Extraction Approach 2

Automatic Recognition of Whale and Dolphin Whistles Based on...

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2nd IEEE International Conference on Power, Electronics and Computer Applications, ICPECA 2022

作者： Wu, Wei Feng, Huibin Junejo, Naveed Ur Rehman Qiu, Yuquan Yan, Jiaquan College of Computer and Control Engineering Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China University of Lahore Department of Computer Engineering Lahore Pakistan

ISBN: (纸本)9781665442763

Automatic recognition of marine mammals plays a significant role in the protection of endangered marine species, generally utilizing their vocalizations. In this paper, we propose a novel visual feature extraction approach for whale and dolphin signals incorporating variational mode decomposition (VMD) and Hilbert transform (VMD-HT) to construct the high-resolution time-frequency signatures and using gray level co-occurrence matrix (GLCM) to extort image features. Firstly, the objected signals are decomposed by VMD algorithm into multiple intrinsic mode functions (IMFs), which can capture local frequency features precisely. Secondly, the time-frequency signature of the objected signal with high resolution is constructed by linear superposition operation of each IMF time-frequency image depicted through Hilbert transform (HT). Thirdly, the image features are extracted using GLCM. Eventually, support vector machine (SVM) is adopted to validate the classification performance of the proposed method. The experimental results verify that the resolution improvement of time-frequency image attains the correct recognition rate and the proposed method accuracy is higher than the compared method about 11.11% © 2022 IEEE.

关键词： Variational mode decomposition

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Reliability assessments of Chinese high speed railway network

Reliability assessments of Chinese high speed railway networ...

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2011 IEEE International Conference on Service Operations, Logistics and Informatics, SOLI 2011

作者： Zhang, Jianhua Hong, Liu Wang, Shuliang Xu, Xiaoming Department of Control Science and Engineering Key Lab for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China University of Shanghai for Science and Technology Shanghai Academy of System Science Shanghai 200093 China

ISBN: (纸本)9781457705731

With the economic developments, high speed railway has been paid many attentions in China and medium- short term planning of Chinese high speed railway network has been formed and most of the railways have been started into operations. In this paper, graph theory and complex network theory are adopted to assess the reliability of Chinese high speed railway network. The topological characteristics and real distances between pairs of stations are discussed to investigate the reliability of Chinese high-speed rail network. Several parameters are presented to investigate the topological characteristics and the reliability and robustness of the network subject to failures. The parameter called unit degree betweenness is proposed to assess the transport capacity of lines connecting with the nodes. The largest degree node-based attacks and the highest betweenness node-based attacks are involved into Chinese high speed railway network to assess the topological reliability and robustness. The results show that the highest betweenness node-based attacks are more effective to destroy the network than the largest degree node-based attacks. Moreover, the cumulative degree distribution and the real mileages of railways between pairs of stations can be fitted by Gauss functions, and the distribution of real shortest distances over all pairs of stations of the network is fitted by a normal distribution function. By the simulations, the critical stations, Guangzhou Station, Zhengzhou Station and Jinan Station for the largest degree node-based attacks, and Wuhan Station, Xuzhou Station and Shijiazhuang Station for the highest betweenness node-based attacks, can be obtained in this paper. © 2011 IEEE.

关键词： Graph theory

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