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混合智能算法
相关语句
  hybrid intelligent algorithm
    A HYBRID INTELLIGENT ALGORITHM FOR LOSS MINIMUM RECONFIGURATION IN DISTRIBUTION NETWORKS
    一种混合智能算法在配电网络重构中的应用
短句来源
    A Hybrid Intelligent Algorithm for Reactive Power Optimization in Electric Power System
    混合智能算法在电力系统无功优化中的应用
短句来源
    This paper introduces the research situation of distribution network reconfiguration algorithms and proposes a novel multi-objective random chance-constrained programming model using hybrid intelligent algorithm to search the best solution.
    针对配电网事故后重构算法进行论述,分析现今国内外已有算法优劣,提出一种新型的多目标随机机会约束规划模型,并应用混合智能算法搜索全局非劣解。
短句来源
    A fuzzy random chance-constrained programming based hybrid intelligent algorithm for quantifying the transmission reliability margin (TRM) is presented.
    提出了基于模糊随机机会约束规划的输电可靠性裕度的数学模型和混合智能算法
短句来源
    Moreover, the hybrid intelligent algorithm for solving this chance-constrained programming model is proposed, and the simulation calculation of the IEEE 30 buses system has been carried out. The advantages, validity and feasibility of the approach proposed are proved by experimental results.
    文中提出的求解该机会约束规划模型的混合智能算法,在IEEE30节点系统上进行了仿真计算,验证了该方法的正确性和可行性。
短句来源
  “混合智能算法”译为未确定词的双语例句
    Hybrid Intelligent Method for Dynamic Reactive Power Optimization
    动态无功优化的混合智能算法
短句来源
    This paper thoroughly have studied thereactive power optimization algorithm, according to the case of algorithm research, thehybrid intelligent algorithm is advised which gets the mutative scale chaos algorithm andthe immune genetic algorithm together, this algorithm has solved the problem of gettinginto the local optimal solution and slow convergence speed for immune geneticalgorithm.
    本文对电力系统无功优化算法进行了深入研究,针对算法研究现状提出将免疫遗传算法与变尺度混沌优化算法进行结合,形成一种混合智能算法,从而解决了免疫遗传算法易陷于局部最优和在接近全局最优解时搜索速度减慢的缺点。
短句来源
    An intelligent optimization algorithm with a combined use of the genetic algorithm and merit-order method is proposed for generation scheduling in bid-based electricity markets.
    针对电力市场下基于竞价的日发电计划的特点 ,提出一种充分结合遗传算法和排队算法各自优点的混合智能算法
短句来源
    A hybrid algorithm that takes full advantages of genetic algorithm (GA) and particle swarm optimization (PSO) is applied to solving this model. Population of the hybrid algorithm is divided into two parts that each evolves separately by using GA and PSO respectively. The optimization information of GA and PSO will be exchanged fully to form a new and tight coupled genetic particle swarm optimization (GPSO).
    针对该优化模型的求解,利用遗传算法(GA)和粒子群优化(PSO)算法相似的优化框架和优化流程,提出一种充分结合GA和PSO算法各自优点的混合智能算法,该算法将群体分成2个子群,分别采用GA和PSO算法进行演化,并充分交换2种算法所获取的优化信息,形成一个紧密耦合的、新型的遗传粒子群优化算法。
短句来源
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  hybrid intelligent algorithm
The designed hybrid intelligent algorithm by embedding the trained neural network into genetic algorithm can optimize the general grey fuzzy programming problems.
      
Finally, one numerical example is provided to illustrate the effectiveness of the model and the hybrid intelligent algorithm.
      
In order to solve general fuzzy programming models, a hybrid intelligent algorithm is also documented.
      
The hybrid intelligent algorithm described in Section 3 was then applied.
      


An intelligent optimization algorithm with a combined use of the genetic algorithm and merit-order method is proposed for generation scheduling in bid-based electricity markets. The genetic algorithm is applied to solve the unit commitment for its outstanding characteristics of global convergence and robustness. The well-known merit-order algorithm is used to determine the dispatching levels of participating generators. The traditional immune genetic algorithm is improved by utilizing expert knowledge for assistance...

An intelligent optimization algorithm with a combined use of the genetic algorithm and merit-order method is proposed for generation scheduling in bid-based electricity markets. The genetic algorithm is applied to solve the unit commitment for its outstanding characteristics of global convergence and robustness. The well-known merit-order algorithm is used to determine the dispatching levels of participating generators. The traditional immune genetic algorithm is improved by utilizing expert knowledge for assistance in searching feasible solutions. The proposed algorithm is applied to a practical system, and numerical results verify the correctness and validity of this method.

针对电力市场下基于竞价的日发电计划的特点 ,提出一种充分结合遗传算法和排队算法各自优点的混合智能算法。该算法利用遗传算法在求解离散组合优化问题上的强收敛性和鲁棒性进行机组优化组合 ,利用排队算法的简洁性和快速性进行经济功率分配。同时 ,利用基于专家知识的免疫遗传算法来提高机组优化组合的计算速度。通过对某实际电力市场基于竞价的日发电计划的计算和分析 ,验证了该算法的正确性和实用性

A new model for distribution maintenance scheduling which intends to find the most economical maintenance schedule without violating any restrictions is proposed in this paper. To solve this complicate problem,this paper presents a hybrid strategy that sufficiently combines the advantages of Immune Algorithm(IA) and Tabu Search(TS). By constructing three effective bacterins which derive from the features of distribution maintenance schedule and introducing TS into mutation operation of IA in the earlier generations,the...

A new model for distribution maintenance scheduling which intends to find the most economical maintenance schedule without violating any restrictions is proposed in this paper. To solve this complicate problem,this paper presents a hybrid strategy that sufficiently combines the advantages of Immune Algorithm(IA) and Tabu Search(TS). By constructing three effective bacterins which derive from the features of distribution maintenance schedule and introducing TS into mutation operation of IA in the earlier generations,the hybrid strategy improves the convergence of optimization and shortens the calculation time. The proposed model and method are applied to a practical system, and numerical results verify the correctness and validity of them.

从配电网设备检修计划编制的实际需要出发,建立了考虑多种约束条件、以配电网经济性最好为目标的检修计划优化模型。针对该模型的特点,提出了一种充分结合免疫算法与禁忌搜索算法优点的混和优化策略,该策略针对配电网检修计划优化问题的特点设计了3种疫苗,并且构造了2阶段变异,在优化前期使用禁忌搜索变异算子,而在优化后期恢复为一般变异算子,从而保证了算法的快速收敛。通过实际计算和分析,验证了文中所提出模型和算法的正确性和实用性,以及与遗传禁忌混合智能算法相比的优越性,实例计算结果表明本文所采用的方法是有效的,免疫禁忌混合智能算法在收敛速度,爬山能力,解的质量和稳定性上都要优于遗传禁忌组合算法,更适合求解配电网检修优化问题。

This paper introduces the research situation of distribution network reconfiguration algorithms and proposes a novel multi-objective random chance-constrained programming model using hybrid intelligent algorithm to search the best solution.The algorithm consists of Monte Carlo,GA and ANN.This model defines the operation time as a random variable and the totle operation time and load as the optimization aim.It uses the chance-constrained inequation to show the importance level of different customers.

针对配电网事故后重构算法进行论述,分析现今国内外已有算法优劣,提出一种新型的多目标随机机会约束规划模型,并应用混合智能算法搜索全局非劣解。模型引入开关操作时间为随机变量,以恢复供电时间最短和恢复供电负荷最大为优化模型目标,应用机会约束不等式表示重要用户的恢复供电次序,将随机模拟、神经元网络和遗传算法结合,设计出混合智能算法求解该多目标随机机会约束规划。

 
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