scholarly journals Population Diversity Maintenance In Brain Storm Optimization Algorithm

2014 ◽  
Vol 4 (2) ◽  
pp. 83-97 ◽  
Author(s):  
Shi Cheng ◽  
Yuhui Shi ◽  
Quande Qin ◽  
Qingyu Zhang ◽  
Ruibin Bai
Keyword(s):  
Swarm Intelligence ◽  
Collective Behavior ◽  
Population Diversity ◽  
Premature Convergence ◽  
Exploration And Exploitation ◽  
Search Results ◽  
Brain Storm Optimization ◽  
Convergence And Divergence ◽  
Definition Of ◽  
The Brain

Abstract The convergence and divergence are two common phenomena in swarm intelligence. To obtain good search results, the algorithm should have a balance on convergence and divergence. The premature convergence happens partially due to the solutions getting clustered together, and not diverging again. The brain storm optimization (BSO), which is a young and promising algorithm in swarm intelligence, is based on the collective behavior of human being, that is, the brainstorming process. The convergence strategy is utilized in BSO algorithm to exploit search areas may contain good solutions. The new solutions are generated by divergence strategy to explore new search areas. Premature convergence also happens in the BSO algorithm. The solutions get clustered after a few iterations, which indicate that the population diversity decreases quickly during the search. A definition of population diversity in BSO algorithm is introduced in this paper to measure the change of solutions’ distribution. The algorithm's exploration and exploitation ability can be measured based on the change of population diversity. Different kinds of partial reinitialization strategies are utilized to improve the population diversity in BSO algorithm. The experimental results show that the performance of the BSO is improved by part of solutions re-initialization strategies.

Population Diversity of Particle Swarm Optimization Algorithm on Solving Single and Multi-Objective Problems

2020 ◽  
pp. 312-344
Author(s):  
Shi Cheng ◽  
Yuhui Shi ◽  
Quande Qin
Keyword(s):  
Particle Swarm Optimization ◽  
Swarm Intelligence ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Population Diversity ◽  
Exploration And Exploitation ◽  
Swarm Optimization ◽  
Diversity Measures ◽  
Computational Resources ◽  
Swarm Intelligence Algorithm

Premature convergence occurs in swarm intelligence algorithms searching for optima. A swarm intelligence algorithm has two kinds of abilities: the exploration of new possibilities and the exploitation of old certainties. The exploration ability means that an algorithm can explore more search places to increase the possibility that the algorithm can find good enough solutions. In contrast, the exploitation ability means that an algorithm focuses on the refinement of found promising areas. An algorithm should have a balance between exploration and exploitation, that is, the allocation of computational resources should be optimized to ensure that an algorithm can find good enough solutions effectively. The diversity measures the distribution of individuals' information. From the observation of the distribution and diversity change, the degree of exploration and exploitation can be obtained.

Experimental Study on Boundary Constraints Handling in Particle Swarm Optimization

2011 ◽  
Vol 2 (3) ◽  
pp. 43-69 ◽  
Author(s):  
Shi Cheng ◽  
Yuhui Shi ◽  
Quande Qin
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Population Diversity ◽  
Premature Convergence ◽  
Exploration And Exploitation ◽  
Swarm Optimization ◽  
Boundary Constraints ◽  
Constraints Handling ◽  
The Impact ◽  
Search Information

Premature convergence happens in Particle Swarm Optimization (PSO) for solving both multimodal problems and unimodal problems. With an improper boundary constraints handling method, particles may get “stuck in” the boundary. Premature convergence means that an algorithm has lost its ability of exploration. Population diversity is an effective way to monitor an algorithm’s ability of exploration and exploitation. Through the population diversity measurement, useful search information can be obtained. PSO with a different topology structure and a different boundary constraints handling strategy will have a different impact on particles’ exploration and exploitation ability. In this paper, the phenomenon of particles gets “stuck in” the boundary in PSO is experimentally studied and reported. The authors observe the position diversity time-changing curves of PSOs with different topologies and different boundary constraints handling techniques, and analyze the impact of these setting on the algorithm’s ability of exploration and exploitation. From these experimental studies, an algorithm’s ability of exploration and exploitation can be observed and the search information obtained; therefore, more effective algorithms can be designed to solve problems.

Population Diversity of Particle Swarm Optimizer Solving Single and Multi-Objective Problems

2012 ◽  
Vol 3 (4) ◽  
pp. 23-60 ◽  
Author(s):  
Shi Cheng ◽  
Yuhui Shi ◽  
Quande Qin
Keyword(s):  
Swarm Intelligence ◽  
Particle Swarm ◽  
Population Diversity ◽  
Exploration And Exploitation ◽  
Adaptive Optimization ◽  
Particle Swarm Optimizer ◽  
Multi Objective ◽  
Multiobjective Problems ◽  
Computational Resources ◽  
Swarm Intelligence Algorithm

Premature convergence occurs in swarm intelligence algorithms searching for optima. A swarm intelligence algorithm has two kinds of abilities: exploration of new possibilities and exploitation of old certainties. The exploration ability means that an algorithm can explore more search place to increase the possibility that the algorithm can find good enough solutions. In contrast, the exploitation ability means that an algorithm focuses on the refinement of found promising areas. An algorithm should have a balance between exploration and exploitation, that is, the allocation of computational resources should be optimized to ensure that an algorithm can find good enough solutions effectively. The diversity measures the distribution of individuals’ information. From the observation of the distribution and diversity change, the degree of exploration and exploitation can be obtained. Another issue in multiobjective is the solution metric. Pareto domination is utilized to compare between two solutions, however, solutions are almost Pareto non-dominated for multi-objective problems with more than ten objectives. In this paper, the authors analyze the population diversity of particle swarm optimizer for solving both single objective and multiobjective problems. The population diversity of solutions is used to measure the goodness of a set of solutions. This metric may guide the search in problems with numerous objectives. Adaptive optimization algorithms can be designed through controlling the balance between exploration and exploitation.

Experimental Study on Boundary Constraints Handling in Particle Swarm Optimization from a Population Diversity Perspective

2015 ◽  
pp. 99-127 ◽  
Author(s):  
Shi Cheng ◽  
Yuhui Shi ◽  
Quande Qin
Keyword(s):  
Particle Swarm Optimization ◽  
Experimental Studies ◽  
Particle Swarm ◽  
Population Diversity ◽  
Premature Convergence ◽  
Exploration And Exploitation ◽  
Swarm Optimization ◽  
Boundary Constraints ◽  
Constraints Handling ◽  
Search Information

Premature convergence happens in Particle Swarm Optimization (PSO) for solving both multimodal problems and unimodal problems. With an improper boundary constraints handling method, particles may get “stuck in” the boundary. Premature convergence means that an algorithm has lost its ability of exploration. Population diversity is an effective way to monitor an algorithm's ability of exploration and exploitation. Through the population diversity measurement, useful search information can be obtained. PSO with a different topology structure and a different boundary constraints handling strategy will have a different impact on particles' exploration and exploitation ability. In this chapter, the phenomenon of particles getting “stuck in” the boundary in PSO is experimentally studied and reported. The authors observe the position diversity time-changing curves of PSOs with different topologies and different boundary constraints handling techniques, and analyze the impact of these settings on the algorithm's abilities of exploration and exploitation. From these experimental studies, an algorithm's abilities of exploration and exploitation can be observed and the search information obtained; therefore, more effective algorithms can be designed to solve problems.

Population Diversity of Particle Swarm Optimizer Solving Single- and Multi-Objective Problems

2015 ◽  
pp. 71-98 ◽  
Author(s):  
Shi Cheng ◽  
Yuhui Shi ◽  
Quande Qin
Keyword(s):  
Swarm Intelligence ◽  
Particle Swarm ◽  
Population Diversity ◽  
Exploration And Exploitation ◽  
Adaptive Optimization ◽  
Particle Swarm Optimizer ◽  
Multiobjective Problems ◽  
Computational Resources ◽  
Swarm Intelligence Algorithm ◽  
Single Objective

Premature convergence occurs in swarm intelligence algorithms searching for optima. A swarm intelligence algorithm has two kinds of abilities: exploration of new possibilities and exploitation of old certainties. The exploration ability means that an algorithm can explore more search places to increase the possibility that the algorithm can find good enough solutions. In contrast, the exploitation ability means that an algorithm focuses on the refinement of found promising areas. An algorithm should have a balance between exploration and exploitation, that is, the allocation of computational resources should be optimized to ensure that an algorithm can find good enough solutions effectively. The diversity measures the distribution of individuals' information. From the observation of the distribution and diversity change, the degree of exploration and exploitation can be obtained. Another issue in multiobjective is the solution metric. Pareto domination is utilized to compare two solutions; however, solutions are almost Pareto non-dominated for multiobjective problems with more than ten objectives. In this chapter, the authors analyze the population diversity of a particle swarm optimizer for solving both single objective and multiobjective problems. The population diversity of solutions is used to measure the goodness of a set of solutions. This metric may guide the search in problems with numerous objectives. Adaptive optimization algorithms can be designed through controlling the balance between exploration and exploitation.

Experimental Study on Boundary Constraint Handling in Particle Swarm Optimization

2013 ◽  
pp. 96-124
Author(s):  
Shi Cheng ◽  
Yuhui Shi ◽  
Quande Qin
Keyword(s):  
Particle Swarm Optimization ◽  
Experimental Studies ◽  
Particle Swarm ◽  
Population Diversity ◽  
Premature Convergence ◽  
Exploration And Exploitation ◽  
Swarm Optimization ◽  
Boundary Constraints ◽  
Constraints Handling ◽  
Search Information

Premature convergence happens in Particle Swarm Optimization (PSO) for solving both multimodal problems and unimodal problems. With an improper boundary constraints handling method, particles may get “stuck in” the boundary. Premature convergence means that an algorithm has lost its ability of exploration. Population diversity is an effective way to monitor an algorithm’s ability of exploration and exploitation. Through the population diversity measurement, useful search information can be obtained. PSO with a different topology structure and a different boundary constraints handling strategy will have a different impact on particles’ exploration and exploitation ability. In this paper, the phenomenon of particles gets “stuck in” the boundary in PSO is experimentally studied and reported. The authors observe the position diversity time-changing curves of PSOs with different topologies and different boundary constraints handling techniques, and analyze the impact of these setting on the algorithm’s ability of exploration and exploitation. From these experimental studies, an algorithm’s ability of exploration and exploitation can be observed and the search information obtained; therefore, more effective algorithms can be designed to solve problems.

Application of Scanning Electron Microscopy to Medical Research

1969 ◽  
Vol 27 ◽  
pp. 12-13
Author(s):  
J. D. Hutchison
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
Medical Research ◽  
Prosthetic Heart Valve ◽  
School Of Medicine ◽  
Transmission Electron ◽  
Definition Of ◽  
Mechanism Of Failure ◽  
The Brain ◽  
Scanning Electron

When the transmission electron microscope was commercially introduced a few years ago, it was heralded as one of the most significant aids to medical research of the century. It continues to occupy that niche; however, the scanning electron microscope is gaining rapidly in relative importance as it fills the gap between conventional optical microscopy and transmission electron microscopy.IBM Boulder is conducting three major programs in cooperation with the Colorado School of Medicine. These are the study of the mechanism of failure of the prosthetic heart valve, the study of the ultrastructure of lung tissue, and the definition of the function of the cilia of the ventricular ependyma of the brain.

Comparison of Fluorine(18)-fluorodeoxyglucose and Gallium(68)-citrate PET/CT in patients with tuberculosis

2019 ◽  
Vol 58 (05) ◽  
pp. 371-378
Author(s):  
Alfred O. Ankrah ◽  
Ismaheel O. Lawal ◽  
Tebatso M.G. Boshomane ◽  
Hans C. Klein ◽  
Thomas Ebenhan ◽  
...  
Keyword(s):  
Tracer Uptake ◽  
Pet Ct ◽  
The Mean ◽  
18F Fdg ◽  
Definition Of ◽  
Gallium 68 ◽  
Attending Physician ◽  
Pet Scans ◽  
The Brain

Abstract 18F-FDG and 68Ga-citrate PET/CT have both been shown to be useful in the management of tuberculosis (TB). We compared the abnormal PET findings of 18F-FDG- and 68Ga-citrate-PET/CT in patients with TB. Methods Patients with TB on anti-TB therapy were included. Patients had a set of PET scans consisting of both 18F-FDG and 68Ga-citrate. Abnormal lesions were identified, and the two sets of scans were compared. The scan findings were correlated to the clinical data as provided by the attending physician. Results 46 PET/CT scans were performed in 18 patients, 11 (61 %) were female, and the mean age was 35.7 ± 13.5 years. Five patients also had both studies for follow-up reasons during the use of anti-TB therapy. Thirteen patients were co-infected with HIV. 18F-FDG detected more lesions than 68Ga-citrate (261 vs. 166, p < 0.0001). 68Ga-citrate showed a better definition of intracerebral lesions due to the absence of tracer uptake in the brain. The mean SUVmax was higher for 18F-FDG compared to 68Ga-citrate (5.73 vs. 3.01, p < 0.0001). We found a significant correlation between the SUVmax of lesions that were determined by both tracers (r = 0.4968, p < 0.0001). Conclusion Preliminary data shows 18F-FDG-PET detects more abnormal lesions in TB compared to 68Ga-citrate. However, 68Ga-citrate has better lesion definition in the brain and is therefore especially useful when intracranial TB is suspected.

DIRECTIONS OF ASSOCIATIVE IDENTIFICATION OF PERSONAL NAMES

2019 ◽  
Vol 18 (28) ◽  
pp. 118-128
Author(s):  
Olena Karpenko ◽  
Tetiana Stoianova
Keyword(s):  
Proper Names ◽  
Mental Lexicon ◽  
Point Of View ◽  
Sound Symbolism ◽  
Personal Names ◽  
Communicative Process ◽  
Proper Name ◽  
Definition Of ◽  
Scientific Value ◽  
The Brain

The article is devoted to the study of personal names from a cognitive point of view. The study is based on the cognitive concept that speech actually exists not in the speech, not in linguistic writings and dictionaries, but in consciousness, in the mental lexicon, in the language of the brain. The conditions for identifying personal names can encompass not only the context, encyclopedias, and reference books, but also the sound form of the word. In the communicative process, during a free associative experiment, which included a name and a recipient’s mental lexicon. The recipient was assigned a task to quickly give some association to the name. The aggregate of a certain number of reactions of different recipients forms the associative field of a proper name. The associative experiment creates the best conditions for identifying the lexeme. The definition of a monosemantic personal name primarily includes the search of what it denotes, while during the process of identifying a polysemantic personal name recipients tend have different reactions. Scientific value is posed by the effect of the choice of letters for the name, sound symbolism, etc. The following belong to the generalized forms of identification: usage of a hyperonym; synonyms and periphrases or simple descriptions; associations denoting the whole (name stimulus) by reference to its part (associatives); cognitive structures such as “stimulus — association” and “whole (stimulus) — part (associative)”; lack of adjacency; mysterious associations. The topicality of the study is determined by its perspective to identify the directions of associative identification of proper names, which is one of the branches of cognitive onomastics. The purpose of the study is to identify, review, and highlight the directions of associative identification of proper names; the object of the research is the names in their entirety and variety; its subject is the existence of names in the mental lexicon, which determines the need for singling out the directions for the associative identification of the personal names.

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