Football Predictions Based on a Fuzzy Model with Genetic and Neural Tuning

A model is proposed for predicting the result of a football match from the previous results of both teams. This model underlies the method of identifying nonlinear dependencies by fuzzy knowledge bases. Acceptable simulation results can be obtained by tuning fuzzy rules using tournament data. The tuning procedure implies choosing the parameters of fuzzy-term membership functions and rule weights by a combination of genetic and neural optimization techniques. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 171–184, July–August 2005.     

遗传算法和模糊控制的融合研究与设计

将遗传算法与模糊控制相结合,能达到取长补短的作用,一方面,模糊控制能够表达非线性和模糊性的系统知识;另一方面,通过遗传算法所拥有的高度并行,随机、全局搜索能力,使控制系统具有了学习能力,提出了先使用模糊逻辑的思想进行交叉概率和变异概率的整定,再利用模糊遗传算法对模糊子集进行了划分,可获得一个基于一定性能指标的次优或最优模糊控制器,又以二阶系统为例进行了计算机仿真,研究结果表明这种方法是有效的。     

基于改进遗传算法的模糊控制器设计

针对模糊控制器的隶属度函数和模糊控制规则的选取及优化缺乏自学习能力与知识采集的手段,以及遗传算法具有自适应、启发式、概率性、迭代式全局收敛的特点,该文章将遗传算法与模糊控制相结合,给出了一种基于改进遗传算法的模糊控制器设计策略.改进算法引入了分裂算子来避免遗传算法在寻优过程中陷入局部最优解,同时对编码方式、选择算子、交叉算子以及变异算子做了相应的调整与改进.并将此改进算法用于优化模糊控制器的隶属度函数与模糊控制规则.仿真结果表明用该改进算法优化后的模糊控制器较用普通遗传算法优化后的模糊控制器具有更好的控制性能.     

Fuzzy Control of HVAC Systems Optimized by Genetic Algorithms

This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers dedicated to the control of heating, ventilating and air conditioning systems concerning energy performance and indoor comfort requirements. This problem has some specific restrictions that make it very particular and complex because of the large time requirements existing due to the need of considering multiple criteria (which enlarges the solution search space) and to the long computation time models require to assess the accuracy of each individual.To solve these restrictions, a genetic tuning strategy considering an efficient multicriteria approach has been proposed. Several fuzzy logic controllers have been produced and tested in laboratory experiments in order to check the adequacy of such control and tuning technique. To do so, accurate models of the controlled buildings (two real test sites) have been provided by experts. Finally, simulations and real experiments were compared determining the effectiveness of the proposed strategy.     

求解模糊Job Shop调度的遗传算法与蚁群算法融合研究

提出一种算法融合策略,解决单一算法求解模糊Job Shop调度问题存在的不足,提高这类问题的求解质量.算法融合策略中,采用遗传算法和蚁群算法进行并行搜索;根据模糊Job Shop调度问题解的特征,提出基于关键工序的邻域选择方法,并将基于这种邻域选择方法的禁忌搜索算法作为局部搜索算法,加强了遗传算法和蚁群算法的局部搜索能力.采用算法融合策略的混合优化算法对以13个难的benchmarks问题经模糊化得到实例进行求解,在较短的时间内,得到的平均满意度较并行遗传算法(PGA)提高5.24%、较TSAB算法提高8.40% .采用算法融合策略构造的混合算法具有较强的搜索能力,说明提出的混合搜索策略是有效的.     

Neurolinguistic identification of nonlinear dependences

A method is proposed for the identification of nonlinear dependences on the basis of a composition of a fuzzy knowledge base and a neural network. The structure of a neurofuzzy network that is isomorphic to a system of linguistic statements of the form “if-then” is specified, and analytical models for training are obtained. The efficiency of the proposed method of identification is illustrated by a computer experiment. Translatedfrom Kibernetika i Sistemnyi Analiz, No. 2, pp. 37–44, March–April, 2000     

基于遗传算法和语言算子的模糊控制器优化研究

用单片机实现模糊控制策略是一种常用的重要的方法,它是根据误差和误差的变化率隶属度函数表,离线计算得到一张模糊控制查询表,用单片机实现查询功能。该方法应用十分广泛,因此优化离散形式的隶属度函数表具有重要的意义。该文提出了一种优化离散形式的隶属度函数表的新方法:即用遗传算法优化模糊集合中的语气算子H,从而优化离散形式隶属函数表。经优化后的隶属函数更能客观地反映控制对象真实特性,从而达到了优化模糊控制器的目的。文章用一个具体的实例以仿真的形式验证了该方法是正确的、有效的。     

Solution of a Diagnostics Problem on the Basis of Fuzzy Relations and a Genetic Algorithm

The use of backward logical inference in expert diagnostic systems is considered. To solve systems of fuzzy logic equations, a genetic algorithm based on the operations of crossover, mutation, and selection of an initial set of chromosomes is proposed. The efficiency of the algorithm proposed is illustrated by computer simulation.