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An investigation of immune detection algorithm with vaccine operator and fuzzy match

An investigation of immune detection algorithm with vaccine ...

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Ya-Jing Zhang Hui-Wen Leng Institute of Computer Science & Technology Yantai University Yantai Shandong China School of Electromechanical and Automobile Engineering Yantai University Yantai Shandong China

Based on research for anomaly detection in the biological immune principles, a change detection algorithm is provided. It synchronizes the idea of negative selection in biology, is applied for the method of scheme match and joins vaccines operator to help detection in this algorithm. And a niching strategy is adopted. This paper discussed the problem of fuzzy match and vaccine operator by comparing the two immune detection algorithms. Shown by experiments, the algorithm improves the problem of hole and keeps variety of antibodies. And its detecting efficiency is increased obviously.

关键词： Detection algorithms Vaccines Immune system Detectors Pathogens Intrusion detection Cloning Biology computing Computer science Automotive engineering

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Research on support vector machine model based on grey relation analysis for daily load forecasting

Research on support vector machine model based on grey relat...

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Dong-Xiao Niu Qiang Wang Jin-Chao Li School of Business Administration North China Electric Power University Baoding China

Regarding to the daily load forecasting, the sample selection and data preprocessing are crucial to its precision. In this paper, the grey relation analysis method is adopted to search the historical data points whose variation trends are the same as the predict point. The variation trend of each point is represented by load values of the neighboring points. As no influencing factors are used in this process, the model is both simple and practical. Finally a support vector machine model is created on the basis of the selected data points. Due to their similar trends of the selected points, the forecasting precision is raised greatly. The present method synthesizes the advantages of grey relation analysis and support vector machine. The practical examples show that the model established in this paper is feasible and effective. Compared with other models, it has a better precision performance and a higher computing speed.

关键词： Support vector machines Predictive models Load forecasting Power system modeling Power system reliability Power system analysis computing Power system planning Power system simulation Weather forecasting Neural networks

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Distributed Service Performance Management Based on Linear Regression and Genetic Programming

Distributed Service Performance Management Based on Linear R...

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Jing Chen Zeng-Zhi Li Zhi-Gang Liao Yun-Lan Wang Telecommunication Engineering Institute Air Force Engineering University Xi'an China Institute of Computer System Architecture & Network Xi'an Jiaotong University Xi'an China Center for High Performance Computing Northwestern Polytechnical University Xi'an China

An architecture for online discovery quantitative models system of service performance management was proposed. The system was capable of constructing the quantitative models without prior knowledge of the managed elements. The model can be updated continuously in response to the changes made in provider configurations and the evolution of business demands. Due to the existence of strong correlation between the distributed service metrics and response times, a linear and a hyper-linear quantitative models are constructed, which respectively use the stepwise multiple linear regression and genetic programming algorithms. The simulation results show that the effectiveness of quantitative model constructing system and model constructing algorithms.

关键词： Linear regression Genetic programming Delay Prototypes Computer network management Telecommunication network management Engineering management Genetic engineering High performance computing Computer architecture

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Parallel robots pose accuracy compensation using artificial neural networks

Parallel robots pose accuracy compensation using artificial ...

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Da-Yong Yu Da-Cheng Cong Jun-Wei Han School of Mechanics and Electronics Engineering Harbin Institute of Technology Harbin China

Parallel robots pose accuracy compensation approach using artificial neural networks has been developed. In this method, an artificial neural network is used with conventional inverse kinematics computation module in parallel. A backpropagation neural network is designed and implemented to learn parallel robot kinematics model error. The trained neural network can be used to performed online pose accuracy compensation in task. Simulation and experimental results for a parallel robot are presented to show the effectiveness of the compensation method based on neural networks.

关键词： Parallel robots Artificial neural networks Robot kinematics Orbital robotics Biological neural networks Computer networks Calibration Concurrent computing Robotic assembly Error correction

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A new form of knowledge representation and reasoning

A new form of knowledge representation and reasoning

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Ming-Hu Ha Yan Li Hai-Jun Li Peng Wang College of Mathematics and Computer Sciences Hebei University Baoding China College of Physics Science and Technology Hebei University Baoding China

The case of the consequence including two or more propositions connected by "AND" or "OR" in the weighted fuzzy production rules (WFPRs) is taken into consideration. Two knowledge representation parameters of input and output weight of a rule are proposed in order to adapt to the new forms of WFPRs. The weighted production rules evaluation method and multilevel fuzzy reasoning method are also improved in this paper. The reasoning consequences and the certainty factors of the consequences can be deduced synchronously after multilevel fuzzy reasoning by using a generalized fuzzy Petri net (GFPN).

关键词： Knowledge representation Fuzzy reasoning Fuzzy systems Hybrid intelligent systems Fuzzy neural networks Fuzzy sets Educational institutions Production systems Mathematics Physics computing

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Verifying person descriptions with term-entity association

Verifying person descriptions with term-entity association

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Su-Jian Li Wen-Jie Li Qin Lu Rui-Feng Xu Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong China

Person description extraction is an important task in biography generation, question answering and summarization, etc. While most of the previous extraction methods mainly depended on structural information, the work presented in the paper focuses on extraction verification by integrating linguistic knowledge provided by HowNet (with semantic knowledge) and the newswire corpus (with statistical information), from which the associations between terms (i.e. the words in HowNet) and person entities are measured. With term-entity association, ineligible descriptions extracted could be filtered out, and a higher precision is achieved in turn.

关键词： Data mining Pattern matching Electronic mail Biographies Information filtering Information filters Natural language processing Web sites Boosting Web pages

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An algorithm for jobs scheduling in computational grid based on time-balancing strategy

An algorithm for jobs scheduling in computational grid based...

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Yan-Li Hu Bao-Xin Xiu Wei-Ming Zhang Wei-Dong Xiao Zhong Liu Sch. of Information System & Management National University of Defense Technology Changsha China

The computational grid provides a promising platform for the efficient execution of parallel coarse grain tasks computing over very large sample space. Scheduling such applications is challenging for the heterogeneity, autonomy, and dynamic adaptability of grid resources. Assuming resource owners have a preemptive priority, we propose an adaptive algorithm of jobs scheduling based on time balancing strategy, which solves the parallel computing tasks by using the idle resources in computational grid. A mathematical model is developed to predict performance, which also considers systems with heterogeneous machine utilization and heterogeneous service distribution. The model separates the influence of machine utilization, job service rate and parallel task allocation on the completion time. According to the time balancing policy, a task is partitioned into several subtasks and scheduled, and the costs of communication are reduced. The expected value of parallel task completion time is predicted with performance model. To get better parallel computing performance, an optimal subset of heterogeneous resources with the shortest parallel executing time of tasks can be selected with the efficient algorithm. Remapping strategy is applied during scheduling, which is more suitable for the dynamic adaptability and domain autonomy in the grid.

关键词： Scheduling algorithm Processor scheduling Grid computing Concurrent computing Dynamic scheduling Parallel processing Adaptive algorithm Mathematical model Costs Predictive models

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Online particle size estimation on one-pass edge detection and particle shape

Online particle size estimation on one-pass edge detection a...

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Wei-Xing Wang Bergholm Department of Computer Science & Technology Chongqing University of Posts and Telecommunications China Department of Scientific Computing University of Uppsala Sweden

In order to quickly and accurately estimate average size of densely packed aggregate particles on a moving conveyor belt, a new image processing method is studied, the method consists of the two major algorithms, the one is one-pass edge detection algorithm, and the other is the average size estimation based on image edge density. The method calculates average particle size without explicit delineating complicated aggregates. To prove the new method, two different aggregate samples were taken for testing, the testing result is satisfactory. The new method is much fast than ordinary particle segmentation algorithm, and is applicable for the image sequence of the densely packed complicated particles.

关键词： Image edge detection Shape Aggregates Image segmentation Belts Image processing machine learning algorithms Testing Inspection Computer science

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Compressing the multirobot team formation state based on SOM network

Compressing the multirobot team formation state based on SOM...

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international conference on machine learning and Cybernetics (icmlc)

作者： Xing-Ce Wang Ping Guo Xin-Yu Liu Jing-Hao Fei College of Information Science and Technology Beijing Normal University Beijing China Institute of Computing Technology Chinese Academy and Sciences Beijing China

As a platform of multirobots' cooperation and coordination, the multirobots team formation is paid more and more attention. Using the reinforcement learning to realize the team formation can strengthen not only the self-learning ability but also the self-adaptation. In this research field, however, there still exit problems such as low learning speed and the difficult convergence raised with the exponential space of reinforcement learning. Using the self-organizing map (SOM) network compressing state from exponential to multinomial speeds up the ergodic, consequently improves the learning rate. And the function of adding and deleting the neurons can compress more space. In the simulation of the experiment, the feasibility of these technologies is verified further. The expands of the methods are strong and can be used in the similar system.

关键词： Orbital robotics Robot sensing systems Robot kinematics State-space methods learning Space technology Neural networks Convergence Neurons Arithmetic

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Comparison of different fusion approaches for network intrusion detection using ensemble of RBFNN

Comparison of different fusion approaches for network intrus...

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international conference on machine learning and Cybernetics (icmlc)

作者： Chan Ng Yeung Tsang Department of Computing Hong Kong Polytechnic University Hong Kong China

The information technology has been adopted to solve problems in network intrusion detection system (IDS) and many approaches have been proposed to tackle the information security problems of computer networks, especially the denial of service (DoS) attacks. The multiple classifier system (MCS) is one of the approaches that has been adopted in the detection of DoS attacks recently. For a MCS to perform better than a single classifier, it is crucial to select the appropriate fusion strategies. Majority vote, average, weighted sum, weighted majority vote, neural network and Dempster-Shafer combination are the fusion strategies that have been widely adopted. The selection of the fusion strategy for a MCS in DoS problem varies widely. In this paper, a comparative study on adopting different fusion strategies for a MCS in DoS problem is provided.

关键词： Intrusion detection Computer crime Neural networks Support vector machines Support vector machine classification Computer networks Voting machine learning Electronic mail Information technology

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