模糊PID和Hopfield神经网络在矿井通风系统中的应用

针对传统的PID控制或者单一的模糊控制无法准确控制矿井通风系统风量的问题,提出了一种采用模糊PID调节器和Hopfield神经网络调节器对矿井通风机的转速、风门、风量进行控制的方法。该方法利用模糊控制器对PID参数进行实时修正,并结合Hopfield神经网络的联想记忆功能和反馈调节特性,实现矿井通风机风量的快速、稳定输出。仿真与实验结果表明,模糊PID调节器和Hopfield神经网络调节器可以准确控制矿井通风机的转速和风量,实现通风系统的稳定输出。     

基于预测决策同态理论的故障数据优化挖掘算法

复杂工程布局方案的设计是一个典型的属带性能约束的布局优化问题,难以求解。针对此类问题,提出了一种人机交互的混合式算法。该算法首先采取人工设计的布局策略,然后与人工蜂群优化算法相结合,构成人机交互的混合算法,这样可以充分发挥人和计算机各自的特长。实例测试和实验对比表明了该算法的可行性和有效性。     

A hybrid metaheuristic approach for the capacitated p-median problem

The capacitated p-median problem (CPMP) seeks to obtain the optimal location of p medians considering distances and capacities for the services to be given by each median. This paper presents an efficient hybrid metaheuristic algorithm by combining a proposed cutting-plane neighborhood structure and a tabu search metaheuristic for the CPMP. In the proposed neighborhood structure to move from the current solution to a neighbor solution, an open median is selected and closed. Then, a linear programming (LP) model is generated by relaxing binary constraints and adding new constraints. The generated LP solution is improved using cutting-plane inequalities. The solution of this strong LP is considered as a new neighbor solution. In order to select an open median to be closed, several strategies are proposed. The neighborhood structure is combined with a tabu search algorithm in the proposed approach. The parameters of the proposed hybrid algorithm are tuned using design of experiments approach. The proposed algorithm is tested on several sets of benchmark instances. The statistical analysis shows efficiency and effectiveness of the hybrid algorithm in comparison with the best approach found in the literature.     

Enhancing the performance of hybrid genetic algorithms by differential improvement

A differential improvement modification to Hybrid Genetic Algorithms is proposed. The general idea is to perform more extensive improvement algorithms on higher quality solutions. Our proposed Differential Improvement (DI) approach is of rather general character. It can be implemented in many different ways. The paradigm remains invariant and can be easily applied to a wider class of optimization problems. Moreover, the DI framework can also be used within other Hybrid metaheuristics like Hybrid Scatter Search algorithms, Particle Swarm Optimization, or Bee Colony Optimization techniques.     

A hybrid meta-heuristic for multi-objective vehicle routing problems with time windows

The Capacitated Vehicle Routing Problem with Time Windows is an important combinatorial optimization problem consisting in the determination of the set of routes of minimum distance to deliver goods, using a fleet of identical vehicles with restricted capacity, so that vehicles must visit customers within a time frame. A large number of algorithms have been proposed to solve single-objective formulations of this problem, including meta-heuristic approaches, which provide high quality solutions in reasonable runtimes. Nevertheless, in recent years some authors have analyzed multi-objective variants that consider additional objectives to the distance travelled. This paper considers not only the minimum distance required to deliver goods, but also the workload imbalance in terms of the distances travelled by the used vehicles and their loads. Thus, MMOEASA, a Pareto-based hybrid algorithm that combines evolutionary computation and simulated annealing, is here proposed and analyzed for solving these multi-objective formulations of the VRPTW. The results obtained when solving a subset of Solomon’s benchmark problems show the good performance of this hybrid approach.     

建立含有受控源网络状态方程的一种系统方法

本文为了适应混合变量法的需要对四种类型的受控源做了相应处理，从而使用混合变量法建立含有受控源网络的状态方程时，不但无需寻找网络的树，而且还具有直接方便，。简便易行，系统性强等优点。     

低CO2排放自然通风建筑的设计与评价——英国谢菲尔德大学学生健康中心

2005年，在约克郡举行的英国皇家建筑师协会RIBA2005庆典上，谢菲尔德大学学生健康中心获得两个奖项？该建筑在设计上特别注重自然采光和自然通风，并使用了低CO2排放环境友好的构件和装饰材料，本文从建筑设计过程阐述其低排放设计策略的发展和贯彻情况，并通过使用后研究评价最初的设计目标是否实现？实际使用效果是否符合预期设计要求，评价内容包括监测部分房间的室内物理状况．了解用户的反应和开窗通风策略的实施情况，评价得到了计算机虚拟环境模拟工具的支持，将现状与现状之外的其他状况进行多方案比较，以提供新的方案解决当前存在的问题，监测和调查显示，该建筑在设计和实际使用方面的确存在一些问题，因此，在计算机模拟和现状监测调查的基础上，本文给用户提出了改进后的自然采光和自然通风操作建议。     

Fe<Subscript>3</Subscript>O<Subscript>4</Subscript>–Au and Fe<Subscript>2</Subscript>O<Subscript>3</Subscript>–Au Hybrid Nanorods: Layer-by-Layer Assembly Synthesis and Their Magnetic and Optical Properties

A layer-by-layer technique has been developed to synthesize FeOOH–Au hybrid nanorods that can be transformed into Fe₂O₃–Au and Fe₃O₄–Au hybrid nanorods via controllable annealing process. The homogenous deposition of Au nanoparticles onto the surface of FeOOH nanorods can be attributed to the strong electrostatic attraction between metal ions and polyelectrolyte-modified FeOOH nanorods. The annealing atmosphere controls the phase transformation from FeOOH–Au to Fe₃O₄–Au and α-Fe₂O₃–Au. Moreover, the magnetic and optical properties of as-synthesized Fe₂O₃–Au and Fe₃O₄–Au hybrid nanorods have been investigated.     

Start‐Up Characteristics of Segmented‐In‐Series Tubular SOFC Power Modules Improved by Catalytic Combustion at Cathodes

For large‐scale SOFC power generation systems, a shorter start‐up time of SOFC cell stacks with relatively large heat capacity is one of the most important technological issues to determine the flexibility in SOFC system operation. In this study, start‐up procedures have been examined to shorten the start‐up time period. The conventional heating procedure using pre‐heated hot air and self‐heating by SOFC operation at low temperatures had a difficulty to shorten the start‐up time period because of the limitation in power generation at lower temperatures. In this study, as an alternative start‐up procedure, catalytic combustion at the SOFC cathodes is, for the first time, demonstrated to be useful on the system level. The applicability of the catalytic combustion to shorten the start‐up time period has been verified numerically as well as experimentally by using a large‐scale cell stack cartridge. This unique start‐up procedure enables to operate SOFC‐based large‐scale power generation systems.     

Degradation-oriented real-time power control of fuel cell hybrid vehicles under uncertain driving conditions

This work provides a real-time power allocation algorithm to address uncertain actual driving situations for fuel cell hybrid vehicles. To predict the vehicle speed under nondeterministic driving conditions, a fusion prediction model is developed based on the advantages of the Markov chain and neural network. The optimal power splitting decision in each receding horizon is then solved using the Pontryagin's minimum principle (PMP) method, considering fuel consumption, State of Charge (SOC), and performance degradation. A degradation model of electrochemical active surface area (ECSA) based on Pt catalyst dissolution was developed. Then the effect of the energy management algorithm on fuel cell degradation was evaluated using the degradation model. Compared with the two conventional real-time power splitting strategies, the approach suggested in this research can better reduce the fuel consumption and maintain the stability of battery SOC with a lower fluctuation while taking into account the degradation of the fuel cell.