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检索条件"任意字段=IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments"

共 233 条记录，以下是11-20 订阅

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Benchmarks for dynamic multi-objective optimisation

Benchmarks for dynamic multi-objective optimisation

引用

2013 ieee symposium on computational intelligence in dynamic and uncertain environments, CIDUE 2013 - 2013 ieee symposium Series on computational intelligence, SSCI 2013

作者： Helbig, Marde Engelbrecht, Andries P. CSIR: Meraka Institute Brummeria South Africa University of Pretoria Computer Science Pretoria South Africa University of Pretoria Computer Science Department Pretoria South Africa

ISBN: (纸本)9781467358491

When algorithms solve dynamic multi-objective optimisation problems (DMOOPs), benchmark functions should be used to determine whether the algorithm can overcome specific difficulties that can occur in real-world problems. However, for dynamic multi-objective optimisation (DMOO) there are no standard benchmark functions that are used. This article proposes characteristics of an ideal set of DMOO benchmark functions, as well as suggested DMOOPs for each characteristic. The limitations of current DMOOPs and studies of dynamic multi-objective optimisation algorithms (DMOAs) are highlighted. In addition, new DMOO benchmark functions with complicated Pareto-optimal sets (POSs) and approaches to develop DMOOPs with either an isolated or deceptive Pareto-optimal front (POF) are introduced to address identified limitations of current DMOOPs. © 2013 ieee.

关键词： Pareto principle

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Analysis of Hyper-heuristic Performance in Different dynamic environments

Analysis of Hyper-heuristic Performance in Different Dynamic...

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ieee symposium on computational intelligence in dynamic and uncertain environments (CIDUE)

作者： van der Stockt, Stefan Engelbrecht, Andries P. Univ Pretoria Computat Intelligence Res Grp Gauteng South Africa

ISBN: (纸本)9781479945153

Optimisation methods designed for static environments do not perform as well on dynamic optimisation problems as purpose-built methods do. Intuitively, hyper-heuristics show great promise in handling dynamic optimisation problem dynamics because hyper-heuristics can select different search methods to employ at different times during the search based on performance profiles. Related studies use simple heuristics in dynamic environments and do not evaluate heuristics that are purpose-built to solve dynamic optimisation problems. This study analyses the performance of a random-based selection hyper-heuristic that manages meta-heuristics that specialise in solving dynamic optimisation problems. The performance of the hyper-heuristic across different types of dynamic environments is investigated and compared with that of the heuristics running in isolation and the same hyper-heuristic managing simple Gaussian mutation heuristics.

关键词： optimisation random processes search problems dynamic environment dynamic optimisation hyperheuristic performance metaheuristics random-based selection static environment Algorithm design and analysis Benchmark testing Heuristic algorithms Optimization Search problems Vectors tabu search Algorithm design and analysis Benchmark testing Heuristic algorithms Stochastic Processes Heuristics Search methods environments

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Multi-Colony Ant Algorithms for the dynamic Travelling Salesman Problem

Multi-Colony Ant Algorithms for the Dynamic Travelling Sales...

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ieee symposium on computational intelligence in dynamic and uncertain environments (CIDUE)

作者： Mavrovouniotis, Michalis Yang, Shengxiang Yao, Xin De Montfort Univ Sch Comp Sci & Informat CCI Leicester LE1 9BH Leics England Univ Birmingham Sch Comp Sci CERCIA Birmingham B15 2TT W Midlands England

ISBN: (纸本)9781479945153

A multi-colony ant colony optimization (ACO) algorithm consists of several colonies of ants. Each colony uses a separate pheromone table in an attempt to maximize the search area explored. Over the years, multi-colony ACO algorithms have been successfully applied on different optimization problems with stationary environments. In this paper, we investigate their performance in dynamic environments. Two types of algorithms are proposed: homogeneous and heterogeneous approaches, where colonies share the same properties and colonies have their own (different) properties, respectively. Experimental results on the dynamic travelling salesman problem show that multi-colony ACO algorithms have promising performance in dynamic environments when compared with single colony ACO algorithms.

关键词： Ant colony optimization

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Ant Colony Optimization with Self-Adaptive Evaporation Rate in dynamic environments

Ant Colony Optimization with Self-Adaptive Evaporation Rate ...

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ieee symposium on computational intelligence in dynamic and uncertain environments (CIDUE)

作者： Mavrovouniotis, Michalis Yang, Shengxiang De Montfort Univ Sch Comp Sci & Informat CCI Leicester LE1 9BH Leics England

ISBN: (纸本)9781479945153

The performance of ant colony optimization (ACO) algorithms in tackling optimization problems strongly depends on different parameters. One of the most important parameters in ACO algorithms when addressing dynamic optimization problems (DOPs) is the pheromone evaporation rate. The role of pheromone evaporation in DOPs is to improve the adaptation capabilities of the algorithm. When a dynamic change occurs, the pheromone trails of the previous environment will not match the new environment especially if the changing environments are not similar. Therefore, pheromone evaporation helps to eliminate pheromone trails that may misguide ants without destroying any knowledge gained from previous environments. In this paper, a self-adaptive evaporation mechanism is proposed in which ants are responsible to select an appropriate evaporation rate while tracking the moving optimum in DOPs. Experimental results show the efficiency of the proposed self-adaptive evaporation mechanism on improving the performance of ACO algorithms for DOPs.

关键词： Evaporation

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Hellinger distance based drift detection for nonstationary environments

Hellinger distance based drift detection for nonstationary e...

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ieee symposium on computational intelligence in dynamic and uncertain environments

作者： Ditzler, Gregory Polikar, Robi Dept. of Electrical and Computer Engineering Rowan University Glassboro NJ United States

ISBN: (纸本)9781424499311

Most machine learning algorithms, including many online learners, assume that the data distribution to be learned is fixed. There are many real-world problems where the distribution of the data changes as a function of time. Changes in nonstationary data distributions can significantly reduce the generalization ability of the learning algorithm on new or field data, if the algorithm is not equipped to track such changes. When the stationary data distribution assumption does not hold, the learner must take appropriate actions to ensure that the new/relevant information is learned. On the other hand, data distributions do not necessarily change continuously, necessitating the ability to monitor the distribution and detect when a significant change in distribution has occurred. In this work, we propose and analyze a feature based drift detection method using the Hellinger distance to detect gradual or abrupt changes in the distribution. © 2011 ieee.

关键词： Learning algorithms

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A Framework of Scalable dynamic Test Problems for dynamic Multi-objective Optimization

A Framework of Scalable Dynamic Test Problems for Dynamic Mu...

引用

ieee symposium on computational intelligence in dynamic and uncertain environments (CIDUE)

作者： Jiang, Shouyong Yang, Shengxiang De Montfort Univ CCI Sch Comp Sci & Informat Leicester LE1 9BH Leics England

ISBN: (纸本)9781479945153

dynamic multi-objective optimization has received increasing attention in recent years. One of striking issues in this field is the lack of standard test suites to determine whether an algorithm is capable of solving dynamic multi-objective optimization problems (DMOPs). So far, a large proportion of test functions commonly used in the literature have only two objectives. It is greatly needed to create scalable test problems for developing algorithms and comparing their performance for solving DMOPs. This paper presents a framework of constructing scalable dynamic test problems, where dynamism can be easily added and controlled, and the changing Pareto-optimal fronts are easy to understand and their landscapes are exactly known. Experiments are conducted to compare the performance of four state-of-the-art algorithms on several typical test functions derived from the proposed framework, which gives a better understanding of the strengths and weaknesses of these tested algorithms for scalable DMOPs.

关键词： Pareto principle

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Real-World dynamic Optimization Using An Adaptive-mutation Compact Genetic Algorithm

Real-World Dynamic Optimization Using An Adaptive-mutation C...

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ieee symposium on computational intelligence in dynamic and uncertain environments (CIDUE)

作者： Uzor, Chigozirim J. Gongora, Mario Coupland, Simon Passow, Benjamin N. De Montfort Univ Ctr Computat Intelligence Leicester Leics England De Montfort Univ DIGITS Leicester Leics England

ISBN: (纸本)9781479945153

While the interest in nature inspired optimization in dynamic environments has been increasing constantly over the past years, evaluations of some of these optimization algorithms are based on artificial benchmark problems. Little has been done to carry-out these evaluation using a real-world dynamic optimization problems. This paper presents a compact optimization algorithm for controllers in dynamic environments. The algorithm is evaluated using a real world dynamic optimization problem instead of an artificial benchmark problem, thus avoiding the reality gap. The experimental result shows that the algorithm has an impact on the performance of a controller in a dynamic environment. Furthermore, results suggest that evaluating the algorithm's candidate solution using an actual real-world problem increases the controller's robustness.

关键词： control system synthesis dynamic programming genetic algorithms performance index stability vibration control PID controller design adaptive-mutation compact genetic algorithm compact optimization algorithm controller performance controller robustness dynamic environment nature inspired optimization real-world dynamic optimization problems torsional mass-spring damper system Microcontrollers Microcontrollers control system synthesis Genetic Algorithm (GA) vibration control performance indicators dynamic programming Optimization algorithms Controllers Benchmark testing controller design

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A memetic algorithm for dynamic economic load dispatch optimization

A memetic algorithm for dynamic economic load dispatch optim...

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2013 ieee symposium on computational intelligence in dynamic and uncertain environments, CIDUE 2013 - 2013 ieee symposium Series on computational intelligence, SSCI 2013

作者： Orike, Sunny Corne, David W. School of Mathematical and Computer Sciences Heriot-Watt University Edinburgh United Kingdom

ISBN: (纸本)9781467358491

The dynamic economic load dispatch (DELD) problem is an extension of the conventional static load dispatch problem in the context of electrical power generation. In the static case, the problem is to optimize the settings for each unit in a generating station so as to supply sufficient power to meet a given overall predicted demand for minimal cost. In the dynamic version of the problem, predicted demand exists for each of a number of successive periods (e.g. 24 hourly periods), and the static version of the problem is to be solved for each period. Until now, the DELD has been treated as a series of static problems. In this paper, we take a memetic algorithm (MA) that has recently provided superior results on some benchmark problems for the static ELD, and we now adapt it for the dynamic case, and investigate a simple dynamic optimization approach to this where the final population of a previous period is used to intialise the population for the next period. This is compared with two baselines, in which (i) the static problems are solved independently, and (ii) the static problems are solved together, treated as a single multi-part problem with suitably adjusted constraints. We evaluate our methods on two benchmark cases of the DELD for which published results exist, and we show that the basic dynamic optimization approach, using our MA, has superior performance to both the baseline approaches and to other approaches published in the literature so far. © 2013 ieee.

关键词： Evolutionary algorithms

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dynamic significant feature extraction for embedded intelligent agent implementations

Dynamic significant feature extraction for embedded intellig...

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2013 ieee symposium on computational intelligence in dynamic and uncertain environments, CIDUE 2013 - 2013 ieee symposium Series on computational intelligence, SSCI 2013

作者： Basterretxea, Koldo Del Campo, Ines Martinez, Maria Victoria Echanobe, Javier Bilbao Basque Country Spain

ISBN: (纸本)9781467358491

'Autonomy' and 'adaptability' are key features of intelligent systems with environment awareness. Many applications of intelligent agents require the processing of information coming in from many available sensors to produce adequate output responses in changing scenarios. For such applications, the concept of autonomy should apply not only to the ability of the agent to produce correct outputs without human guidance, but also to its potential ubiquity and portability. However, processing complex computational intelligence algorithms in small, low-power embedded systems, very often with tight delay constraints, is a challenging engineering problem. In this paper a computationally efficient neuro-fuzzy information processing paradigm is tested in an ambient intelligent scenario to evaluate its appropriateness for future embedded SoC (System on Chip) implementations. The system has been endowed with an information preprocessing module based on Principal Component Analysis (PCA) that produces reduced input space dimensionalities with little loss of modeling power. An eventual on-chip PCA module could be applied to dynamically update the reduced meaningful space of information from the outside world. Moreover, the applicability of the PCA module to obtain a fault-tolerant agent in the presence of sensor failures has also been investigated with satisfactory results. © 2013 ieee.

关键词： Principal component analysis

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Performance Evaluation of Sensor-Based Detection Schemes on dynamic Optimization Problems

Performance Evaluation of Sensor-Based Detection Schemes on ...

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ieee symposium on computational intelligence in dynamic and uncertain environments (CIDUE)

作者： Altin, Lokman Topcuoglu, Haluk Rahmi Marmara Univ Dept Comp Engn TR-34722 Istanbul Turkey

ISBN: (纸本)9781479945153

Most of the real world optimization problems in different domains demonstrate dynamic behavior, which can be in the form of changes in the objective function, problem parameters and/or constraints for different time periods. Detecting the points in time where a change occurs in the landscape is a critical issue for a large number of evolutionary dynamic optimization techniques in the literature. In this paper, we present an empirical study whose focus is the performance evaluation of various sensor-based detection schemes by using two well known dynamic optimization problems, which are moving peaks benchmark (MPB) and dynamic knapsack problem (DKP). Our experimental evaluation by using two dynamic optimization problem validates the sensor-based detection schemes considered, where the effectiveness of each scheme is measured with the average rate of correctly identified changes and the average number of sensors invoked to detect a change.

关键词： dynamic programming evolutionary computation knapsack problems sensors DKP MPB dynamic knapsack problem dynamic optimization problems evolutionary dynamic optimization techniques moving peaks benchmark performance evaluation point detection sensor-based detection schemes Benchmark testing Detectors Optimization Sociology Statistics Vehicle dynamics Performance Evaluation knapsack problems Benchmark testing Androgenetic Alopecia Sociology Vehicle dynamics evolutionary algorithm dynamic programming Sensors dynamical Problem

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