在矿浆过滤预处理中表面活性剂的应用

针对钼矿的基本物性,筛选合适的表面活性剂,进行钼矿浆过滤条件的试验研究。结果表明,钼矿浆中加入合适的表面活性剂后,增加了滤饼厚度,降低了滤饼湿含量,提高了对矿浆的处理能力。     

A survey on nature-inspired optimization algorithms with fuzzy logic for dynamic parameter adaptation

Metaheuristic optimization algorithms have become a popular choice for solving complex problems which are otherwise difficult to solve by traditional methods. However, these methods have the problem of the parameter adaptation and many researchers have proposed modifications using fuzzy logic to solve this problem and obtain better results than the original methods. In this study a comprehensive review is made of the optimization techniques in which fuzzy logic is used to dynamically adapt some important parameters in these methods. In this paper, the survey mainly covers the optimization methods of Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Ant Colony Optimization (ACO), which in the last years have been used with fuzzy logic to improve the performance of the optimization methods.     

Optimisation of partner selection and collaborative transportation scheduling in Virtual Enterprises using GA

Partner selection and transportation scheduling are critical to the success of a Virtual Enterprise. Collaborative transportation is a promising strategy that can help many enterprises survive and thrive in today’s highly competitive market. To help decision makers establish and operate Virtual Enterprises more effectively, an innovative decision support system is proposed in this paper. First, new model for integration of partner selection and collaborative transportation scheduling in Virtual Enterprises is developed. This integrated optimisation problem is very dynamic in nature and it is required to optimise a number of interlinked sub-problems at the same time. Then, a novel Genetic Algorithm with a unique dynamic chromosome representation and genetic operations is developed to find an optimal solution to the integrated problem. The effectiveness of the proposed approach is demonstrated in a representative case study.     

用混合式遗传算法进行给水管网现状分析

将广义简约梯度法(GRG)思想应用于传统遗传算法,提出一种新的混合式遗传算法(HGA),此方法具有很强的全局和局部搜索能力,并且无需复杂的编码、解码过程,可以准确解决多变量、多峰值的给水管网现状分析问题。采用此算法,绝大多数的计算值与实测值的误差可减小到1%以下,能准确反映管网的实际工况。     

蔬菜配送系统的路径优化及设计开发

蔬菜配送对时效性有很高的要求,配送路径优化成为企业赢利的关键点,而路径优化是NP难问题,传统的算法不能在有限的时间内给出最优解。使用蚁群算法（Ant Colony Optimization,AC0）并对其参数进行优化,解决车辆配送路径优化问题,使得配送路径实时最优化,降低配送成本和企业经营成本。本系统使用Struts2、Hibernate、Spring三大框架进行设计,前台具有智能定位、配送体系、订单跟踪、价格动态功能,后台集成用户管理、订单管理、新闻管理、蔬菜管理、客服服务功能。系统采用模块化设计,具有结构清晰,易于扩展的优点。     

《数据结构与算法》教学方法改革探讨

《数据结构与算法》是理论与实践并重的计算机专业的核心课程,该课程理论和实践知识体系难度均较大,学生反映课程枯燥难学、兴趣匮乏。针对目前学生的学习过程中遇到的困难,结合应用型人才培养目标、学生及课程的特点,对教学方法进行多方面的探讨,提出案例教学、加强学生课堂参与度、重视理论与实践紧密结合、多种手段辅助教学、以赛促学、上机考试考核制度等教学方法。     

发电企业竞价上网博弈模型及其算法研究

假设所有发电企业通过密封报价这种形式来上网竞价,并在发电企业共同见证及同一时刻开标,且规定报价最低者将会被选为中标方,设计两个发电企业竞价上网的基于静态贝叶斯理论的博弈模型以及算法,当参与的发电企业均应用线性策略时,对模型所对应的收敛性进行了分析,同时对贝叶斯纳什均衡解是否存在进行了讨论;接下来对两个发电企业竞价上网模型予以相应扩展,分析了若干个发电企业竞价条件下的贝叶斯纳什均衡及相关问题,与此同时,构建了一个包含若干发电企业在内的共同竞价上网博弈模型;最后借助计算机系统予以仿真实验,得到的结论是：在电力竞价上网的博弈模型中,随着企业数量的不断增加,各自报价将会更加理性,并不断趋于预测值。     

Adaptive Linear Dynamic Matrix Control applied to an integrating process

Dynamic Matrix Control (DMC) has proven to be a powerful tool for optimal regulation of chemical processes under constrained conditions. It is based on a linear convolution model derived from step-response measurements. A model predictive control algorithm optimises closed-loop performance for a nominal operating point. However, as the process moves away from this point, control usually becomes sub-optimal due to process non-linearity. As seen in this work, the DMC algorithm can be made adaptive, to establish a new local model, by recursive estimation of the local step response parameters from normal plant variations. However, when used for control of plants containing integrating process units, steady-state offsets occur for sustained changes. Thus, a novel Adaptive Linear Dynamic Matrix Control (ALDMC) algorithm has been developed and used to control a 2-input/2-output system with an integrating behaviour. Comparisons of model control and plant control with and without these features demonstrated the importance of integral compensation for integrating processes, and model adaptation in the case of plant/model mismatch. Some cross-compensation of integration by the adaptive feature was also noted. An holistic technique is demonstrated which simultaneously recognises residual integration disturbances and matrix parameter variations, whereas previous techniques which recognise only one of these will fail in the presence of the other.     

Pt-V2O5-WO3/TiO2 catalysts supported on SiC filter for NO reduction at low temperature

The catalytic filter, V₂O₅-WO₃-TiO₂ supported on a ceramic filter, is known as a promising material for treating particulates and NO _x simultaneously at optimum temperatures around 320°C. In order to improve its catalytic activity at low temperatures, the effect of Pt addition on the catalytic filter has been investigated. Catalytic filters, Pt-V₂O₅-WO₃-TiO₂/SiC, were prepared by co-impregnation of Pt, V, and W precursors on TiO₂ coated-SiC filter by vacuum aided-dip coating. The Pt-added catalytic filter shifted the optimum working temperature from 280–330°C (for the non Pt-impregnated filter) to 180–230°C, providing N _x slip concentration less than 20 ppm for the treatment of 700 ppm NO at a face velocity of 2 cm/s with the same value over the non Pt-added catalytic filters. The promotional effect following the addition of Pt is believed to result from electrical modification of the catalyst maintaining a high electron transfer state. Ammonia oxidation was also observed to be dominant above the optimal temperature for SCR.     

Learning Natural Colors for Image Recoloring

We present a data‐driven method for automatically recoloring a photo to enhance its appearance or change a viewer's emotional response to it. A compact representation called a RegionNet summarizes color and geometric features of image regions, and geometric relationships between them. Correlations between color property distributions and geometric features of regions are learned from a database of well‐colored photos. A probabilistic factor graph model is used to summarize distributions of color properties and generate an overall probability distribution for color suggestions. Given a new input image, we can generate multiple recolored results which unlike previous automatic results, are both natural and artistic, and compatible with their spatial arrangements.