scholarly journals An Improved Teaching-Learning-Based Optimization with the Social Character of PSO for Global Optimization

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Feng Zou ◽  
Debao Chen ◽  
Jiangtao Wang
Keyword(s):  
Optimization Problems ◽  
Global Solutions ◽  
Function Optimization ◽  
Improved Method ◽  
Social Character ◽  
The Social ◽  
Teaching Learning Based Optimization ◽  
The Mean ◽  
The Individual ◽  
Teaching Learning

An improved teaching-learning-based optimization with combining of the social character of PSO (TLBO-PSO), which is considering the teacher’s behavior influence on the students and the mean grade of the class, is proposed in the paper to find the global solutions of function optimization problems. In this method, the teacher phase of TLBO is modified; the new position of the individual is determined by the old position, the mean position, and the best position of current generation. The method overcomes disadvantage that the evolution of the original TLBO might stop when the mean position of students equals the position of the teacher. To decrease the computation cost of the algorithm, the process of removing the duplicate individual in original TLBO is not adopted in the improved algorithm. Moreover, the probability of local convergence of the improved method is decreased by the mutation operator. The effectiveness of the proposed method is tested on some benchmark functions, and the results are competitive with respect to some other methods.

The Subjective Present and Its Modulation in Clinical Contexts

2013 ◽  
Vol 1 (2) ◽  
pp. 239-259 ◽  
Author(s):  
Wolfgang Tschacher ◽  
Fabian Ramseyer ◽  
Claudia Bergomi
Keyword(s):  
Perceptual Grouping ◽  
Statistical Significance ◽  
Temporal Distribution ◽  
Future Research ◽  
Implicit Processes ◽  
The Social ◽  
Gestalt Perception ◽  
Psychotherapeutic Techniques ◽  
The Mean ◽  
The Individual

Time is a basic dimension in psychology, underlying behavior and experience. Timing and time perception constitute implicit processes that are often inaccessible to the individual person. Research in this field has shown that timing is involved in many areas of clinical significance. In the projects presented here, we combine timing with seemingly different fields of research, such as psychopathology, perceptual grouping, and embodied cognition. Focusing on the time scale of the subjective present, we report findings from three different clinical studies: (1) We studied perceived causality in schizophrenia patients, finding that perceptual grouping (‘binding’, ‘Gestalt formation’), which leads to visual causality perceptions, did not distinguish between patients and healthy controls. Patients however did integrate context (provided by the temporal distribution of auditory context stimuli) less into perceptions, in significant contrast to controls. This is consistent with reports of higher inaccuracy in schizophrenia patients’ temporal processing. (2) In a project on auditory Gestalt perception we investigated auditory perceptual grouping in schizophrenia patients. The mean dwell time was positively related to how much patients were prone to auditory hallucinations. Dwell times of auditory Gestalts may be regarded as operationalizations of the subjective present; findings thus suggested that patients with hallucinations had a shorter present. (3) The movement correlations of interacting individuals were used to study the non-verbal synchrony between therapist and patient in psychotherapy sessions. We operationalized the duration of an embodied ‘social present’ by the statistical significance of such associations, finding a window of roughly 5.7 seconds in conversing dyads. We discuss that temporal scales of nowness may be modifiable, e.g., by mindfulness. This yields promising goals for future research on timing in the clinical context: psychotherapeutic techniques may alter binding processes, hence the subjective present of individuals, and may affect the social present in therapeutic interactions.

scholarly journals An Entropy-Based Approach to Portfolio Optimization

Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 332 ◽  
Author(s):  
Peter Joseph Mercurio ◽  
Yuehua Wu ◽  
Hong Xie
Keyword(s):  
Objective Function ◽  
Portfolio Optimization ◽  
Historical Data ◽  
Optimization Problems ◽  
Improved Method ◽  
Financial Industry ◽  
New Family ◽  
The Mean ◽  
Mean Variance Portfolio ◽  
Mean Variance

This paper presents an improved method of applying entropy as a risk in portfolio optimization. A new family of portfolio optimization problems called the return-entropy portfolio optimization (REPO) is introduced that simplifies the computation of portfolio entropy using a combinatorial approach. REPO addresses five main practical concerns with the mean-variance portfolio optimization (MVPO). Pioneered by Harry Markowitz, MVPO revolutionized the financial industry as the first formal mathematical approach to risk-averse investing. REPO uses a mean-entropy objective function instead of the mean-variance objective function used in MVPO. REPO also simplifies the portfolio entropy calculation by utilizing combinatorial generating functions in the optimization objective function. REPO and MVPO were compared by emulating competing portfolios over historical data and REPO significantly outperformed MVPO in a strong majority of cases.

Synthesis of thinned planar antenna arrays using teaching–learning-based optimization

2014 ◽  
Vol 7 (5) ◽  
pp. 557-563 ◽  
Author(s):  
Nihad I. Dib
Keyword(s):  
Antenna Arrays ◽  
Optimization Problems ◽  
Optimization Method ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Planar Antenna ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Level Reduction ◽  
Better Than

In this paper, the design of thinned planar antenna arrays of isotropic radiators with optimum side lobe level reduction is studied. The teaching–learning-based optimization (TLBO) method, a newly proposed global evolutionary optimization method, is used to determine an optimum set of turned-ON elements of thinned planar antenna arrays that provides a radiation pattern with optimum side lobe level reduction. The TLBO represents a new algorithm for optimization problems in antenna arrays design. It is shown that the TLBO provides results that are better than (or the same as) those obtained using other evolutionary algorithms.

scholarly journals Synthesis of Thinned Concentric Circular Antenna Arrays Using Modified TLBO Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Zailei Luo ◽  
Xueming He ◽  
Xuedong Chen ◽  
Xin Luo ◽  
Xiaoqing Li
Keyword(s):  
Antenna Arrays ◽  
Optimization Problems ◽  
Extended Space ◽  
Half Wavelength ◽  
Tlbo Algorithm ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Antenna Array Synthesis ◽  
Circular Antenna Arrays ◽  
Circular Antenna Array

Teaching-learning-based optimization (TLBO) algorithm is a new kind of stochastic metaheuristic algorithm which has been proven effective and powerful in many engineering optimization problems. This paper describes the application of a modified version of TLBO algorithm, MTLBO, for synthesis of thinned concentric circular antenna arrays (CCAAs). The MTLBO is adjusted for CCAA design according to the geometry arrangement of antenna elements. CCAAs with uniform interelement spacing fixed at half wavelength have been considered for thinning using MTLBO algorithm. For practical purpose, this paper demonstrated SLL reduction of thinned CCAAs in the whole regular and extended space other than the phi = 0° plane alone. The uniformly and nonuniformly excited CCAAs have been discussed, respectively, during the simulation process. The proposed MTLBO is very easy to be implemented and requires fewer algorithm specified parameters, which is suitable for concentric circular antenna array synthesis. Numerical results clearly show the superiority of MTLBO algorithm in finding optimum solutions compared to particle swarm optimization algorithm and firefly algorithm.

scholarly journals Optimization using evolutionary metaheuristic techniques: a brief review

2018 ◽  
Vol 15 (1) ◽  
pp. 44-53 ◽  
Author(s):  
Sajja Radhika ◽  
Aparna Chaparala
Keyword(s):  
Optimization Problems ◽  
Real Life ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Life Problems ◽  
Evolutionary Metaheuristic ◽  
Teaching Learning Based Optimization ◽  
Metaheuristic Techniques ◽  
Teaching Learning

Optimization is necessary for finding appropriate solutions to a range of real life problems. Evolutionary-approach-based meta-heuristics have gained prominence in recent years for solving Multi Objective Optimization Problems (MOOP). Multi Objective Evolutionary Approaches (MOEA) has substantial success across a variety of real-world engineering applications. The present paper attempts to provide a general overview of a few selected algorithms, including genetic algorithms, ant colony optimization, particle swarm optimization, and simulated annealing techniques. Additionally, the review is extended to present differential evolution and teaching-learning-based optimization. Few applications of the said algorithms are also presented. This review intends to serve as a reference for further work in this domain.

scholarly journals TEACHING EXPERIENCES IN THE DEVELOPMENT OF THE COMMUNICATION COMPETENCE IN STUDENTS WITH COGNITIVE DISABILITY

2020 ◽  
Vol LXVIII (2) ◽  
pp. 181-201
Author(s):  
Mădălina-Maria Vasiliu
Keyword(s):  
Students With Disabilities ◽  
Adult Life ◽  
Communication Competence ◽  
Learning Needs ◽  
Cognitive Disability ◽  
Best Value ◽  
The Social ◽  
The Individual ◽  
Teaching Learning ◽  
Intellectual Potential

The current analysis starts from a teacher’s experience with cognitively disabled students. In such cases, the management of the teaching-learning process is challenged by the limitations of various activities (generalizations, abstraction or inductive-deductive operations). In these situations, the teacher has to select effective activities for developing the competences in the curriculum. In this context, success could only be obtained if proper attention is given to the individual learning needs of each student. At the same time, an emotional relationship that is based on trust needs to be developed between the teacher and the students and their parents. The communication competence is a priority since it is absolutely necessary for the social integration of students with disabilities as it provides the means to express feelings, needs and views. The challenge to plan adequate teaching strategies is correlated with understanding the child’s real issue and its timely solution: the more serious the cognitive disability, the later speech develops and remains at a low level in the adult life, generating difficulties in expressing thought and emotion. If the youngsters experience a false disability triggered by the lack of educational stimulation or if they have an authentic cognitive disability, these students need sustained support. The examples of interventions we present in this paper come from our attempts to best value the intellectual potential of these children and, consequently, to find solutions for a differentiated adaptation to each child’s needs by planning competence-oriented creative teaching activities.

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