Swarm intelligence for mixed-variable design optimization

Many engineering optimization problems frequently encounter continuous variables and discrete variables which adds considerably to the solution complexity.Very few of the existing methods can yield a globally optimal solution when the objective functions are non-convex and non-differentiable.This paper presents a hybrid swarm intelligence approach(HSIA)for solving these nonlinear optimization problems which contain integer,discrete,zero-one and continuous variables.HSIA provides an improvement in global search reliability in a mixed-variable space and converges steadily to a good solution.An approach to handle various kinds of variables and constraints is discussed.Comparison testing of several examples of mixed-variable optimization problems in the literature showed that the proposed approach is superior to current methods for finding the best solution,in terms of both solution quality and algorithm robustness.     

Swarm intelligence for mixed-variable design optimization

INTRODUCTION Most nonlinear optimization methods assumethat objective function variables are continuous.However, many practical engineering designproblems frequently encounter discrete variables aswell as continuous variables. Discrete variables areused in many ways such as the representation of theset of standard sized components, the decision onthe number of identical parts or the choice betweendifferent design options. For example, the numberof the teeth of a gear must be chosen …     

Multiple objective particle swarm optimization technique for economic load dispatch

INTRODUCTION The conventional economic load dispatch prob-lem of power generation involves allocation of power generation to different thermal units to minimize the operating cost subject to diverse equality and ine-quality constraints of the power system. This makes the economic load dispatch problem a large-scale highly non-linear constrained optimization problem. However, as a result of public awareness of envi-ronmental protection, diverse emission compliance strategies have emerged (…     

群智能算法及其应用

群智能算法是一种新兴的演化计算技术,它已经成功地被运用于许多领域。实践证明,群智能方法是一种能够解决许多全局优化问题的有效方法。本文介绍了群智能理论的产生和发展过程,并着力阐述群智能理论中的两个主要算法（粒子群算法和蚁群算法）的算法思想以及研究现状。     

电力系统经济负荷分配的改进混沌粒子群算法

提出一种用于电力系统经济负荷分配的改进混沌粒子群算法．算法中采用自适应外罚函数法解决目标函数的约束问题,考虑了机组的系统平衡、出力上下限、爬坡速率和工作死区等约束条件;在粒子群算法中引入混沌机制,使算法能快速跳出局部极值区,提高算法的全局寻优性能;针对变惯性权重系数和变最大搜索速度改进措施的不足,提出依据机组爬坡速率约束来缩小最优解的搜索区域．仿真结果表明,改进的混沌粒子群算法对于解决带约束条件的经济负荷分配问题是可行和高效的,与改进前的计算方法相比,降低了运行费用,提高了寻优速度．     

Optimal coordinated voltage control of power systems

INTRODUCTION Voltage security control as an indispensable fa- cility in power systems aims at mid or long term voltage quality maintenance of power systems in the presence of load and/or transmission line disturbances. Most results of earlier research have been reported on transient stabilization and network control for voltage security of power systems, with various techniques originated from modern control methodology such as dynamic programming (Popovic et al., 2002; Wu et al., 2001), …     

基于商业智能的电网负荷预测模型的构建研究

根据对电网负荷预测业务的分析,采用探索型数据分析方法对电力企业数据仓库中的数据进行训练建模,构建出电网负荷预测模型。模型应用情况表明:应用该模型后电力企业负荷预测较传统预测方法准确率明显提高,电力企业预测技术水平相应提高,同时,应用该模型还有助于电力企业有计划地进行用电管理,确保电力企业决策分析可行性。     

一种新型的配电网线损管理及无功优化系统

介绍一套集配电网络的图形编辑、线损计算分析、无功优化以及报表管理一体化的系统,可基于图形和SCA-DA系统实时数据共享,接入配变监测、负荷控制系统,整合成完整的线路或台区数据,包括设备属性以及各种实时运行数据等.采用改进强引导粒子群与混沌优化相结合的算法进行无功优化.该算法解决传统粒子群寻优后期粒子可能陷入早熟收敛的问题.通过对福建某高压配电网的具体计算,最优降损率可以达到14.04%,节点最低电压从0.895 0（p.u.）提高到0.995 6（p.u.）,系统通过一种新型线损管理及无功优化模式,为工作人员提供一个决策支持的技术平台.     

岳阳电网的现状及其系统优化的意义

配电网是电力系统的重要组成部分。随着岳阳电网的飞速发展,配电网的结构和运行情况日趋复杂。配电网直接面向用户,设备众多,分布面广,而系统损耗也主要集中在配电环节。因此,研宄岳阳电网的优化运行方法,对提高岳阳电网运行的经济效率具有重大意义。     

无功补偿技术在配电网上的应用

论述无功补偿技术现状，无功补偿装置的优、缺点，以及基于智能控制策略的TSC的发展，阐述合理运用配电网的无功补偿技术，能够有效地维持电力系统的电压水平，减少线路功耗和降低有功网损，提高网络输送容量，减少发电费用，提高电力城网建设效率．     

电力电子技术与运动控制系统课程的优化整合

针对电力电子技术和运动控制系统课程的特点及教学中的问题,提出对两门课程教学内容进行优化整合,注重交叉与衔接。在课程教学中采用多种教学方法及先进教学手段,重视两门课程实践教学体系建设,注意优化创新,促进学生对课程内容的掌握与巩固。实践表明这是提高课程教学质量和学生综合素质的有效方式。     

社会权力来源的法哲学研究路径

学术史上对社会权力来源的研究基本上通过两条路径展开:即价值判断的路径和事实判断的路径.每条路径都有其合理之处,因此在研究社会权力来源时,把价值判断与事实判断进行有机结合,才是符合马克思主义的做法.     

Personality traits and general intelligence as predictors of academic performance: A structural equation modelling approach

The aim of the present study was to investigate the extent to which personality traits, after controlling for general intelligence, predict academic performance in different school subjects. Upper secondary school students in Sweden (N = 315) completed the Wonderlic IQ test (Wonderlic, 1992) and the IPIP-NEO-PI test (Goldberg, 1999). A series of hierarchical structural equation models showed that general intelligence, Conscientiousness, Extraversion and Neuroticism were significantly linked to overall academic performance. There were also different findings for a lower level of personality traits, e.g. different personality traits were associated with different subjects. The findings are discussed with regard to previous results on personality traits as determinants of academic performance in different school subjects and the fact that lower level traits may facilitate achievement in particular subjects.     

Participant or spectator? Comprehending the willingness of faculty to use intelligent tutoring systems in the artificial intelligence era

The advancement of technology, especially the development and application of artificial intelligence, has deeply affected the education sector and brought opportunities for pedagogical adaptation. Intelligent tutoring systems, a major application of artificial intelligence in education, have drawn extensive concerns. However, in reality, the penetration rate of intelligent tutoring systems and the enthusiasm of faculty to use are still relatively low. This research examined the determinants of the willingness of faculty to use intelligent tutoring systems. Innovation diffusion theory was the theoretical basis of this research and it was adapted by incorporating perceived trust and experience. To gather data, a cross-sectional questionnaire survey was performed and structural equation modeling was employed to analyze the data. The findings indicated that relative advantage, compatibility, perceived trust and experience are the contributing determinants of the willingness of faculty to use intelligent tutoring systems, while complexity has no significant effect. Meanwhile, complexity is significantly negatively affected by experience and compatibility. Relative advantage is significantly positively affected by perceived trust but not by complexity. Based on the research findings, relevant recommendations for encouraging faculty to use intelligent tutoring systems were proposed.     

A new digital approach to design multivariable robust optimal control systems

This paper presents a new design of robust optimal controller for multivariable system. The row characteristic functions of a linear multivariable system and dynamic decoupling of its equivalent system, were applied to change the transfer function matrix of a closed-loop system into a normal function matrix, so that robust H∞optimal stability is guaranteed. Furthermore, for the decoupled equivalent control system the l∞optimization approach is used to have the closed-loop system embody optimal time domain indexes. A successful application on a heater control system verified the excellence of the new control scheme.     

Using manipulatives to support an embodied approach to learning trigonometry in a South African school: A case study

ABSTRACT

Multiple Intelligence Theory suggests that individuals perceive knowledge in eight different ways. This article reports on a study that explored the role of manipulatives in the teaching and learning of trigonometric ratios in grade 10. The approach attempts in addressing three domains of the Multiple Intelligence Theory (linguistic/verbal intelligence, logical/mathematical intelligence and spatial intelligence). The foundation of this research was a case study contained in the interpretative paradigm involving five grade 10 mathematics pupils at a high school in South Africa. The data was collected from: (1) activity sheet containing written responses of pupils; (2) observations; and (3) semi-structured interviews. The data was analysed and it was found that the use of manipulatives in teaching and learning mathematics played a positive role in leaners understanding of trigonometric ratios at grade 10 level. In general the findings of this study supported other research findings that confirm that manipulatives were important mediating tools in the development of conceptual and procedural understanding of mathematical concepts. Besides these pedagogical implications the study proved that the manipulatives effectively consolidated the features of Lesh's model.     

基于双频控制技术的有源电力滤波器分析及应用研究

有源电力滤波器作为对治理电力谐波很有前途的方法,因其功率器件水平限制了APF单元的容量、投入电网运行后的的稳定性问题、以及初装成本高等三个方面啄因限制了APF的大量运用特别是在大功率等级的运用。以后的研究方向是提高补偿容量、降低APF的成本以及解决有源电力滤波器的稳定性问题。为了解决这三个方面的问题,本文提出双频控制有源电力滤波器的新解决方案,用一个低频APF与一个高频APF组合运行。双频控制APF采用低频APF来主要输出功率,可以用低频器件GTO等,这样就可以提高功率等级,提高在现有器件水平下的容量。同时因为低频单元处理功率,系统效率可以大为提高,可靠性也将进一步提高。相对于多重化等拓扑结构而言,系统成本也将大大降低。而高频APF不主要承担处理功率的任务,可以采用IGBT工作在高频,这样就可以提高系统的补偿性能。     

Using natural language processing to support peer-feedback in the age of artificial intelligence: A cross-disciplinary framework and a research agenda

Advancements in artificial intelligence are rapidly increasing. The new-generation large language models, such as ChatGPT and GPT-4, bear the potential to transform educational approaches, such as peer-feedback. To investigate peer-feedback at the intersection of natural language processing (NLP) and educational research, this paper suggests a cross-disciplinary framework that aims to facilitate the development of NLP-based adaptive measures for supporting peer-feedback processes in digital learning environments. To conceptualize this process, we introduce a peer-feedback process model, which describes learners' activities and textual products. Further, we introduce a terminological and procedural scheme that facilitates systematically deriving measures to foster the peer-feedback process and how NLP may enhance the adaptivity of such learning support. Building on prior research on education and NLP, we apply this scheme to all learner activities of the peer-feedback process model to exemplify a range of NLP-based adaptive support measures. We also discuss the current challenges and suggest directions for future cross-disciplinary research on the effectiveness and other dimensions of NLP-based adaptive support for peer-feedback. Building on our suggested framework, future research and collaborations at the intersection of education and NLP can innovate peer-feedback in digital learning environments.

Practitioner notes

What is already known about this topic

• There is considerable research in educational science on peer-feedback processes.
• Natural language processing facilitates the analysis of students' textual data.
• There is a lack of systematic orientation regarding which NLP techniques can be applied to which data to effectively support the peer-feedback process.

What this paper adds

• A comprehensive overview model that describes the relevant activities and products in the peer-feedback process.
• A terminological and procedural scheme for designing NLP-based adaptive support measures.
• An application of this scheme to the peer-feedback process results in exemplifying the use cases of how NLP may be employed to support each learner activity during peer-feedback.

Implications for practice and/or policy

• To boost the effectiveness of their peer-feedback scenarios, instructors and instructional designers should identify relevant leverage points, corresponding support measures, adaptation targets and automation goals based on theory and empirical findings.
• Management and IT departments of higher education institutions should strive to provide digital tools based on modern NLP models and integrate them into the respective learning management systems; those tools should help in translating the automation goals requested by their instructors into prediction targets, take relevant data as input and allow for evaluating the predictions.

     

Teleology as a tacit dimension of teaching and learning evolution: A sociological approach to classroom interaction in science education

Teleology has been described as an intuitive cognitive bias and as a major type of student conception. There is controversy regarding whether teleological explanations are a central obstacle to, are legitimate in, or are even supportive of science learning. However, interaction in science classrooms has not yet been investigated with regard to teleology. Consequently, this study addresses the question of how teleological explanations emerge in science classroom interactions about evolution and how teachers and students address emerging teleology. In this article, we introduce a theoretical and methodological framework drawing from the sociology of knowledge and systems theory, suggesting that this framework may enrich the understanding of knowledge construction and of social practices in the science classroom because it enables distinguishing between explicit and tacit knowledge. We investigated seven secondary school units about evolution and present data from four grade-12 classes in Germany, a country with very few creationists, to contrast two ways in which teleology is addressed. In the first type, the teachers combine intentional and need-based teleological explanations with aspects of scientific theories in an ambiguous way. Contrastingly, in the second type, the teachers construct a duality between correct mechanistic and incorrect teleological explanations by discrediting preceding scientific theories. In the discussion, we argue that the presented sociological approach can also be valuable in other science education contexts, such as creationism, the nature of science and socio-scientific issues, because classroom interaction involves tacit communication, such as a tacit epistemology, which are essential grounds for the students' knowledge construction.