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检索条件"主题词=A* optimization algorithm"

共 938 条记录，以下是31-40 订阅

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Research on Power Systema* optimization algorithm Frameworks Empowered by Machine Learning 39

Research on Power System Optimization Algorithm Frameworks E...

引用

39th Youth Academic Annual Conference of Chinese-Association-of-Automation (YAC)

作者： Shi, Zhan Yan, Dong Tian, Jie Lu, Yudong Wang, Xinying China Electric Power Research Institute Artificial Intelligence Application Research Center Beijing China State Grid Zhejiang Electric Power Co. Ltd. Electric Power Research Institute Hangzhou China

ISBN: (纸本)9798350390780;9798350379228

In recent years, with the increasing complexity of system structure and refinement of management, power system optimization computation is facing the double pressure of computational accuracy and computational time. Machine learning (M) techniques can effectively utilize vast historical data to provide new theoretical basis for optimizing stable and fast solutions. This paper is aimed to summarize thea* optimization algorithm frameworks, which is based on the interaction between M and optimization computing for general power system optimization problems. The framework empowered by M mainly includes end-to-end optimization, ML-enhanced optimization, and joint-driven optimization. By utilizing the physical characteristics of power system, these frameworks not only provide a more efficient and reliable calculation scheme for the optimal operation of power system, but also provide innovative solutions for other complex optimization problems.

关键词： power system optimization algorithm machine learning artificial intelligence

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Efficient Microwave Wireless Power Transmission usinga* optimization algorithm 16

Efficient Microwave Wireless Power Transmission using Optimi...

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16th European Conference on Antennas and Propagation (EuCAP)

作者： Kim, Ho Yeol Nam, Sangwook Seoul Natl Univ Sch Elect & Informat Engn Seoul South Korea

ISBN: (纸本)9788831299046

In this study, we developed an efficient microwave wireless power transmission (MPT) system for multiple receivers using an optimization (OPT) technique. Thea* optimization algorithm finds the optimal transmission signal for transferring the desired power to multiple receivers with maximum power transfer efficiency (PTE). We designed a 5 x 5 rectangular patch array antenna and patch element antenna operating at 10 GHz as the transmitter and receiver, respectively. The operating process of the MPT system using the OPT technique is analyzed. Additionally, we compared the received power of each receiver and the PTE of the OPT technique with that of the multi-receiver time-reversal (MR-TR) technique considering various scenarios. The OPT algorithm generates a multibeam to charge multiple receiver simultaneously. We validated that the OPT technique can deliver power to receivers precisely at desired ratios with greater PTE than that of the MR-TR technique in an MPT system.

关键词： microwave wireless power transmission array antenna optimization algorithm

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An immunity-baseda* optimization algorithm for tuning neuro-fuzzy controller

An immunity-based optimization algorithm for tuning neuro-fu...

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International Conference on Machine Learning and Cybernetics

作者： Zuo, XQ Li, SY Ban, XJ Harbin Inst Technol Dept Control Sci & Engn Harbin 50001 Peoples R China

ISBN: (纸本)0780378652

Immune evolutionary algorithm is proposed based on the evolutionary principle in the immune system. In the algorithm, two new parameters of expansion radius and mutation radius are defined to construct a small neighborhood and a large neighborhood. Then expansion and mutation operations are designed to perform local and global search respectively by using the two neighborhoods, thus, two-level neighborhood search mechanism is realized. The results of multi-modal function optimization show that the algorithm has nice global and local searching performances. The algorithm is employed to design a neuro-fuzzy controller for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due to multivariable inputs, state variable synthesis scheme is suggested to reduce the number of fuzzy rules. Experimental results show that the designed controller can control actual inverted pendulum successfully.

关键词： artificial immune system evolutionary algorithm genetic algorithm optimization algorithm neuro-fuzzy controller

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Ana* optimization algorithm for Improving Combined Multi-Stage Deep Drawing and Ironing Processes of Axisymmetric Components. Analysis and Experimentation 36

An Optimization Algorithm for Improving Combined Multi-Stage...

引用

36th International MATADOR Conference

作者： Ramirez, Francisco Javier Domingo, Rosario Sebastian, Miguel Angel Univ Castilla La Mancha Sch Adv Comp Engn Albacete Spain Natl Distance Univ UNED Dept Mfg Engn Madrid Spain

ISBN: (纸本)9781849964319

A newa* optimization algorithm for combined processes of deep-drawing and ironing has been created in order to improve these types of axisymmetric components manufacturing procedures. The model provides a comprehensive analysis of those phenomena occurring in multi-stage processes of axisymmetric geometry work pieces. The scientific development starts out from works that provide LDR (limiting drawing ratio) solutions based on normal anisotropy value, strain hardering exponent and others parameters which have just been applied to the drawing and redrawing stages so far. The authors extend this work to the ironing stages, and also provide a global and integral scientific solution for the whole process. At the beginning the algorithm provides an initial solution which is afterwards optimized by means of objective functions and constraints. The resolution of the optimization process is carried out by a recursive function that minimizes the total time of the global process. The enhanced solution performs a significant reduction in time and costs of the process. The model allows the modification and correction of certain process variables in order to predict the impact of those that are not fully controllable. The final results are compared using experimental results obtained by the authors, so as to show the reliability of the complete solution.

关键词： optimization algorithm Deep drawing Ironing Limiting drawing ratio Aided system Intelligent manufacturing

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Adaptive Bayesiana* optimization algorithm for Unpredictable Business Environments. 24

Adaptive Bayesian Optimization Algorithm for Unpredictable B...

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8th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (ISMSI)

作者： Maitra, Sarit Alliance Univ Alliance Business Sch Bengaluru India

ISBN: (纸本)9798400717291

This paper introduces an adaptive Bayesian optimization (BayesOpt) framework with dynamic conditioning and jitter mechanisms. The new framework enhances the adaptability and effectiveness of optimization in unpredictable business environments. The dynamic scaling in this framework dynamically modifies the mean objective function in each iteration, and adaptive conditioning functions. The adaptive acquisition jitter function enhances adaptability by adjusting the jitter of the acquisition function. The framework is tested using single-objective, multi-objective, and decoupled multiobjective functions. Statistical analyses which include t-statistics, p-values, and effect size measures (Cohen's d and Hedges g) reveal the superiority of the proposed framework over the original Bayes optimization. The primary contribution is developing a novel and effective optimization approach in stochastic environments, especially in the context of supply chain inventory management.

关键词： Adaptive conditioning Dynamic scaling Effect size optimization algorithm Probabilistic modeling Stochastic environments

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Digital audio codec based on the improveda* optimization algorithm of adaptive wavelets and dynamic bits allocation scheme

Digital audio codec based on the improved optimization algor...

引用

3rd International Conference on Signal Processing (ICSP 96)

作者： Xiong, XB Zhao, EY Department of Telecommunications Engineering Beijing University슠of Posts and슠Telecommunications

ISBN: (纸本)7505338900

This paper presents the idea ofa* optimization algorithm of adaptive wavelets that can improve the coding algorithm to decrease the computation complexity to ten percent of that presented in the paper[5]. The full optimization of adaptive wavelets is replaced by the new method, in which the optimization is divided into two cascaded steps. And the entropy-coding-based quantization of side information is adopted so that tile bit rate is significantly reduced because it accounts for a plenty of percent of bit costs. The bit rate can decrease about 15 percent of that presented ill paper [8] by taking the method. It also coordinates with psycho-acoustics model and dynamic bits allocation scheme to make the coding noise inaudible under the condition of the least bits cost.

关键词： digital communication codecs audio coding entropy codes quantisation (signal) adaptive signal processing wavelet transforms optimisation computational complexity digital audio codec optimization algorithm adaptive wavelets dynamic bit allocation coding algorithm computational complexity reduction entropy coding based quantization side information bit rate reduction psychoacoustics model coding noise bit costs

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Artificial Glowworm Swarma* optimization algorithm for Solving 0-1 Knapsack Problem

Artificial Glowworm Swarm Optimization Algorithm for Solving...

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International Conference on Smart Materials and Intelligent Systems

作者： Gong, Qiaoqiao Zhou, Yongquan Yang, Yan Guangxi Univ Nationalities Coll Math & Comp Sci Nanning 530006 Guangxi Peoples R China

ISBN: (纸本)9780878492237

In this paper, an artificial glowworm swarma* optimization algorithm for solving 0-1 knapsack problem is proposed, and the detailed realization of the algorithm is illustrated. According to intelligent algorithm for knapsack problem, the question of sensitive parameter's choice is avoided under the greed idea. Simulation results show that the artificial glowworm swarma* optimization algorithm for solving 0-1 knapsack problems is feasible and effective.

关键词： Artificial glowworm swarm algorithm optimization algorithm 0-1 knapsack problems

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An entropy-based model to support QoS multicast routinga* optimization algorithm for mobile ad hoc networks

An entropy-based model to support QoS multicast routing opti...

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International Conference on Wireless Communications, Networking and Mobile Computing

作者： Sun, BL Li, LY Chen, H Wuhan Univ Technol Sch Comp Sci & Technol Wuhan 430063 Peoples R China

ISBN: (纸本)078039335X

A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links. There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic nature of the network topology and restricted resources, quality of service (QoS) and multicast routing in MANET is a challenging task. In this paper, we present an entropy-based model to support QoS multicast routinga* optimization algorithm in mobile ad hoc networks (EQMOA). The basic motivations of the proposed modeling approach stem from the commonality observed in the location uncertainty in mobile ad hoc wireless networks and the concept of entropy. The simulation results demonstrate that the proposed approach and parameters provide an accurate and efficient method of estimating and evaluating the route stability in dynamic mobile networks.

关键词： ad hoc network entropy multicast routing optimization algorithm

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A distributed entropy-based QoS multicast routinga* optimization algorithm for MANET

A distributed entropy-based QoS multicast routing optimizati...

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6th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT 2005)

作者： Gui, C Sun, BL Hubei Univ Econ Dept Comp & Elect Sci Wuhan 430205 Peoples R China

ISBN: (纸本)0769524052

A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic nature of the network topology and restricted resources, quality of service (QoS) and multicast routing in MANET is a challenging task In this paper, we present an entropy-based model to support QoS multicast routinga* optimization algorithm in mobile ad hoc networks (EQMOA). The basic motivations or the proposed modeling approach stem from the commonality observed in the location uncertainty in mobile ad hoc wireless networks and the concept of entropy. The simulation results demonstrate that the proposed approach and parameters provide an accurate and efficient method of estimating and evaluating the route stability in dynamic mobile networks.

关键词： Ad Hoc network QoS multicast routing entropy optimization algorithm

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Competition Over Resources: A Newa* optimization algorithm Based on Animals Behavioral Ecology 6

Competition Over Resources: A New optimization Algorithm Bas...

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2014 International Conference on Intelligent Networking and Collaborative Systems (IEEE INCoS 2014)

作者： Mohseni, Sina Gholami, Reza Zarei, Niloofar Zadeh, Arash Roomi Noshirvani Univ Technol Fac Elect Engn Babol Sar Iran Amirkabir Univ Technol Fac Elect Engn Tehran Iran Polytech Univ Turin Dept Automat & Comp Sci Turin Italy

ISBN: (纸本)9781479963874

In the recent years, many heuristica* optimization algorithms have been developed. A majority of these heuristic algorithms have been derived from the behavior of biological or physical systems in nature. In this paper, we propose a newa* optimization algorithm based on competitive behavior of animal groups. In the proposed algorithm, the whole population is divided into a number of groups. In each group, the best searching agent spreads its children in its owned territory. Any group which is not able to find rich resources will be eliminated form competition. The competition gradually results in an increase in population of wealthy group which gives a fast convergence to proposeda* optimization algorithm. In the following, after a detailed explanation of the algorithm and pseudo code, we compare it to other existing algorithms, including genetics and particle swarm optimizations. Applying the proposed algorithm on various benchmark cost functions, shows faster and superior results compared to othera* optimization algorithms.

关键词： optimization algorithm animals behavioral ecology nature inspired algorithm

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