A Partial Parallel Airport Gate Assignment Supported by a Knowledge－based System Combined with Mathematical Programming

The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.

Inference of General Mass Action-Based State Equations for Oscillatory Biochemical Reaction Systems Using <i>k</i>-Step Genetic Programming

Systems biology requires the development of algorithms that use omics data to infer interaction networks among biomolecules working within an organism. One major type of evolutionary algorithm, genetic programming (GP), is useful for its high heuristic ability as a search method for obtaining suitable solutions expressed as tree structures. However, because GP determines the values of parameters such as coefficients by random values, it is difficult to apply in the inference of state equations that describe oscillatory biochemical reaction systems with high nonlinearity. Accordingly, in this study, we propose a new GP procedure called “k-step GP” intended for inferring the state equations of oscillatory biochemical reaction systems. The k-step GP procedure consists of two algorithms: 1) Parameter optimization using the modified Powell method—after genetic operations such as crossover and mutation, the values of parameters such as coefficients are optimized by applying the modified Powell method with secondary convergence. 2) GP using divided learning data—to improve the inference efficiency, imposes perturbations through the addition of learning data at various intervals and adaptations to these changes result in state equations with higher fitness. We are confident that k-step GP is an algorithm that is particularly well suited to inferring state equations for oscillatory biochemical reaction systems and contributes to solving inverse problems in systems biology.

A Stochastic Programming Strategy in Microgrid Cyber Physical Energy System for Energy Optimal Operation

This paper focuses on the energy optimal operation problem of microgrids (MGs) under stochastic environment. The deterministic method of MGs operation is often uneconomical because it fails to consider the high randomness of unconventional energy resources. Therefore, it is necessary to develop a novel operation approach combining the uncertainty in the physical world with modeling strategy in the cyber system. This paper proposes an energy scheduling optimization strategy based on stochastic programming model by considering the uncertainty in MGs. The goal is to minimize the expected operation cost of MGs. The uncertainties are modeled based on autoregressive moving average (ARMA) model to expose the effects of physical world on cyber world. Through the comparison of the simulation results with deterministic method, it is shown that the effectiveness and robustness of proposed stochastic energy scheduling optimization strategy for MGs are valid. © 2014 Chinese Association of Automation.

Stability of Nonlinear Systems Using Optimal Fuzzy Controllers and Its Simulation by Java Programming

In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPSO) is implemented to optimize the fuzzy controller parameters in order to decrease the distance error of the cart and summation of the angle errors of the pendulums, simultaneously. The feasibility and efficiency of the proposed Pareto front is assessed in comparison with results reported in literature and obtained from other algorithms.Finally, the Java programming with applets is utilized to simulate the stability of the nonlinear system and explain the internetbased control.

A Neuron-Oriented Programming System

A neruon-oriented programming system based on parallel neural information processing has been presented. With the neural programming system built upon 4～8 process elements(TMS C30), the system has thus provided users high speed, general purpose and large scale neural network application development platforms etc.

C-Language Programming for Development of Conventional Water Treatment Plants Decision Support System

Water-Decision Support System (DSS) tools enhance decision-makings towards improved water supply in a given region. The rigours of manual design of the conventional water treatment plants are easily eliminated with the use of softwares as in the case of DSS. Therefore, this paper focuses on the development of a Water-DSS for design of treatment plant in Karkala Town, Udupi District of India. A four-decade population projection was made using the baseline data of 1971 till date. The manual computation for water demand, unit operations and adjoining facilities was carried out and later coded in C-programming language for development of a DSS for easier design and process selection. Data validation was done and results from the two approaches were compared. With the C-programming technique, a decision support tool for design and process selection of drinking water treatment plant using conventional method has been developed and named Water-DSS1. The designed tool is simple, accurate, flexible, efficient and universal, easily adaptable to any similar conventional treatment plant. Water-DSS1 is thus recommended for general use in ultimately alleviating water supply challenges.

Modeling Dynamic Systems by Using the Nonlinear Difference Equations Based on Genetic Programming

When acquaintances of a model are little or the model is too complicate to build by using traditional time series methods, it is convenient for us to take advantage of genetic programming (GP) to build the model. Considering the complexity of nonlinear dynamic systems, this paper proposes modeling dynamic systems by using the nonlinear difference e-quation based on GP technique. First it gives the method, criteria and evaluation of modeling. Then it describes the modeling algorithm using GP. Finally two typical examples of time series are used to perform the numerical experiments. The result shows that this algorithm can successfully establish the difference equation model of dynamic systems and its predictive result is also satisfactory.

Intelligent Tutoring System of Linear Programming

There is a growing technological development in intelligent teaching systems. This field has become interesting to many researchers. In this paper, we present an intelligent tutoring system for teaching mathematics that helps students understand the basics of linear programming using Linear Program Solver and Service for Solving Linear Programming Problems, through which students will be able to solve economic problems. It comes down to determining the minimum or maximum value of a linear function, which is called the objective function, according to pre-set limiting conditions expressed by linear equations and inequalities. The goal function and the limiting conditions represent a mathematical model of the observed problem. Working as a professor of mathematics in high school, I felt the need for one such work and dealing with the study of linear programming as an integral part of mathematics. There are a number of papers in this regard, but exclusively related to traditional ways of working, as stated in the introductory part of the paper. The center of work as well as the final part deals with the study of linear programming using programs that deal with this topic.

Optimal Control for a Class of Complex Singular System Based on Adaptive Dynamic Programming

This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method, controllers for solving the singular systems optimal control problem are designed. The proposed algorithm can work well when the system model is not exactly known but the input and output data can be measured. The policy iteration of each controller only uses their own states and input information for learning,and do not need to know the whole system dynamics. Simulation results on the New England 10-machine 39-bus test system show the effectiveness of the designed controller.

基于知识图谱推荐系统的高校“汇编语言程序设计”课程教学改革

随着现代教育技术的迅速发展,“汇编语言程序设计”课程的传统教学模式亟待创新,以满足学生的多元化学习需求。知识图谱推荐系统结合知识图谱和学生模型构建,实现了教学内容的个性化推荐、学习路径规划、资源整合、多样化的教学互动。为验证知识图谱推荐系统在“汇编语言程序设计”教学中的作用进行实证研究。研究结果表明,知识图谱推荐系统能有效提高学生的学习成绩、学习兴趣和学习满意度,为教学方法的创新和优化提供有益的参考。

基于云-TOPSIS-灰关联分析模型的产品服务系统方案评价技术

方案评价是产品服务系统设计的关键环节之一,评价结果的合理性对企业发展至关重要。基于最小平方和法,构建了云-TOPSIS-灰关联分析模型,对产品服务系统方案进行评价。引入云模型和相对偏好关系量化离散型指标,解决专家评价的模糊性和随机性问题。运用TOPSIS灰关联分析法确定正、负理想灰关联系数矩阵,集成指标权重和正、负理想灰关联系数矩阵建立正、负理想加权灰关联系数矩阵,兼顾了几何方案序列曲线的位置接近度和形状相似度。运用最小平方和法求解灰关联投影系数,确定方案排序。以某农业装备企业拖拉机产品服务系统方案评价为实例,验证了所提模型的科学性和可行性。

Research and Development on NC System of Gear-hobbing Machine based on Zero-programming Technology

By the analysis of roller gear processing technology, combining with gear meshing mechanism and motion relationship, models for rolling gear machining parameter and zero-programming are established. In this paper, the automatic generation technology of NC program for CNC gear machining process has been studied and the zero-programming system architecture of open CNC gear-hobbing machine has been presented. In the design and development of the system, human computer interaction, programming algorithm and the design of each function module have bean done. Application test shows that the expected design requirements have been achieved.

微服务架构在国家级免疫规划信息系统中的应用

目的/意义全民接种疫苗背景下,通过微服务架构技术路线,重构国家级免疫规划信息系统。方法/过程采用领域驱动方法设计业务模型,基于微服务重构信息系统,详细阐述系统构建过程,包括对象识别与定义、领域重组与聚合、服务拆分、系统部署应用及效果对比。结果/结论从功能性和非功能性两方面,对系统数据采集、数据解析处理、数据校验、数据消费与存储等多个方面进行总体评价,评价结果显示通过微服务架构的改造,系统功能完善与性能提升效果显著。

Optimal Redundancy Allocation in Hierarchical Series-Parallel Systems Using Mixed Integer Programming

Reliability optimization plays an important role in design, operation and management of the industrial systems. System reliability can be easily enhanced by improving the reliability of unreliable components and/or by using redundant configuration with subsystems/components in parallel. Redundancy Allocation Problem (RAP) was studied in this research. A mixed integer programming model was proposed to solve the problem, which considers simultaneously two objectives under several resource constraints. The model is only for the hierarchical series-parallel systems in which the elements of any subset of subsystems or components are connected in series or parallel and constitute a larger subsystem or total system. At the end of the study, the performance of the proposed approach was evaluated by a numerical example.

基于学习通和在线判题系统的程序设计课程考核系统研究

程序设计课程是大部分工科专业的基础课程,对后续专业课程学习非常重要。为了提高课程的教学效果,结合学习通和在线判题系统对课程内容、实践环节等进行研究与探索,根据学校教学特点设计了一款在线判题系统。该系统基于ThinkPHP框架搭建,使用目前流行的B/S架构,最终以网页形式提供给教师与学生实践操作。学生通过该系统能获得测评实时反馈,增强了学习自主性,提高了编程能力,并减少了教师的工作量。

Control strategy optimization using dynamic programming method for synergic electric system on hybrid electric vehicle

Dynamic Programming (DP) algorithm is used to find the optimal trajectories under Beijing cycle for the power management of synergic electric system (SES) which is composed of battery and super capacitor. Feasible rules are derived from analyzing the optimal trajectories, and it has the highest contribution to Hybrid Electric Vehicle (HEV). The methods of how to get the best performance is also educed. Using the new Rule-based power management strat-egy adopted from the optimal results, it is easy to demonstrate the effectiveness of the new strategy in further improvement of the fuel economy by the synergic hybrid system.

计及电制氢和碳捕集的园区综合能源系统动态规划

“碳达峰,碳中和”目标对综合能源系统提出了低碳高效的新要求。针对园区综合能源系统的源-网-荷-储联合规划问题,基于Bellman最优理论将系统净收益最大化的规划模型进行分解,建立“风光储协同-多能互联耦合-能源消纳制氢-最优碳捕集”的多阶段动态规划模型并求解设备的最佳配置方案。结果表明,该模型在经济性和环保性方面具有显著优势,电制氢收益可观并促进电能就地消纳,碳捕集降低了系统碳排放并具有售卖CO_(2)气体和碳配额的双重收益,同时在动态规划过程中达到了最佳的电制氢配置和最优的碳捕集比例。

基于遗传程序水闸综合智能化控制系统的设计

提出了一种基于遗传程序的水闸综合智能化控制系统,旨在解决传统水闸控制系统中由于一对一布线导致的可靠性问题。研究涵盖了系统的硬件设计包括通信功能与监控界面,以及软件设计特别是利用遗传程序确定控制目标的传递函数和设计回路控制器。通过实验测试,结果显示该控制系统显著降低了元件总故障率,提高了闸门开度控制的准确性,增强了系统的可靠性。这一发现证明了遗传程序技术在智能化控制系统中的应用价值,为水闸控制系统的设计和优化提供了新的方向。

中国音乐教育话语体系内涵与构建——基于1952年以来普通高等学校本科专业目录调整的历时性观察

学界目前对“音乐教育”话语体系的理解有着不同声音。回顾相关学术史不难发现,音乐教育话语体系的构建是一个系统工程,需要政府和高校、管理者和教师等多方共同努力。1952年以来,政府通过调整高等学校本科专业目录等手段,紧紧把握音乐教育的话语权。2021年本科音乐教育专业的增设是高等音乐师范教育专业的回归,也是音乐教育学学科建设的新发展。为构建新时代中国特色音乐教育话语体系,建议政府要充分发挥主导力量,各利益攸关方戮力同心办好音乐教育专业,共同构建一体化的学科专业人才培养体系。音乐教育话语体系构建是持续、开放、发展的话题,需要学界共同参与讨论。