Research on Chaos Theory Improved Evolutionary Algorithm

2014 ◽  
Vol 926-930 ◽  
pp. 3463-3466
Author(s):  
Shu Qun Liu ◽  
Yang Zhou ◽  
Wei Ping Yan
Keyword(s):  
Evolutionary Algorithm ◽  
Chaos Theory ◽  
Global Search ◽  
Convergence Speed ◽  
Mutation Operator ◽  
Running Time ◽  
Algorithm Convergence ◽  
The Relationship

Because the basic evolutionary algorithm convergence speed is slow, prone to stagnation, the algorithm running time is too long, so according to chaos theory about the relationship between evolution and chaos, this paper design an improved evolutionary algorithm with chaotic mutation operator, the optimization of the contraction policy can improve the global search ability of effective, significantly improved the performance of the proposed algorithm.

A K-Means Clustering Algorithm Based on Enhanced Differential Evolution

2011 ◽  
Vol 339 ◽  
pp. 71-75 ◽  
Author(s):  
Li Mao ◽  
Huai Jin Gong ◽  
Xing Yang Liu
Keyword(s):  
Differential Evolution ◽  
Numerical Experiments ◽  
Clustering Algorithm ◽  
Global Search ◽  
Convergence Speed ◽  
Mutation Operator ◽  
Local Optima ◽  
Initial Cluster ◽  
Crossover Probability ◽  
Probability Operator

The conventional k-means algorithms are sensitive to the initial cluster centers, and tend to be trapped by local optima. To resolve these problems, a novel k-means clustering algorithm using enhanced differential evolution technique is proposed in this paper. This algorithm improves the global search ability by applying Laplace mutation operator and exponentially increasing crossover probability operator. Numerical experiments show that this algorithm overcomes the disadvantages of the conventional k-means algorithms, and improves search ability with higher accuracy, faster convergence speed and better robustness.

Intervento: Psicoterapia e ricerca "scientifica"

2009 ◽  
pp. 77-94
Author(s):  
Paolo Migone
Keyword(s):  
Key Words ◽  
Empirical Research ◽  
Chaos Theory ◽  
Scientific Research ◽  
Psychotherapy Research ◽  
Clinical Material ◽  
History Of Psychotherapy ◽  
History Of ◽  
The Relationship

- Some problems of the relationship between psychotherapy and scientific research are examined. The following aspects are discussed: the theory of demarcation between science and non-science, the problem of replicability, "hard" and "soft" sciences, complexity and chaos theory, the levels of probability and indeterminacy, the inductive-deductive circle, abduction, etc. Clinical material is presented in order to exemplify the issues under discussion. Some of the problems met by empirical research in psychotherapy (for example the manualization of psychotherapy techniques) are described, and the phases of the history of psychotherapy research movement are summarized. (This intervention is a discussion of the paper by the physicist Ferdinando Bersani "Replicability in science: Myth or reality?". Psicoterapia e Scienze Umane, 2009, XLIII, 1: 59-76). [KEY WORDS: science, psychotherapy research, epistemology, replicability, psychoanalytic research]

Particle Swarm Optimization Algorithm with Mutation Operator for Particle Filter Noise Reduction in Mechanical Fault Diagnosis

2020 ◽  
Vol 34 (10) ◽  
pp. 2058012 ◽  
Author(s):  
Hanxin Chen ◽  
Dong Liang Fan ◽  
Lu Fang ◽  
Wenjian Huang ◽  
Jinmin Huang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Filter ◽  
Noise Reduction ◽  
Real Time ◽  
Particle Swarm ◽  
Utilization Rate ◽  
Mutation Operator ◽  
Swarm Optimization ◽  
Running Time ◽  
Filter Noise

In this paper, a new particle swarm optimization particle filter (NPSO-PF) algorithm is proposed, which is called particle cluster optimization particle filter algorithm with mutation operator, and is used for real-time filtering and noise reduction of nonlinear vibration signals. Because of its introduction of mutation operator, this algorithm overcomes the problem where by particle swarm optimization (PSO) algorithm easily falls into local optimal value, with a low calculation accuracy. At the same time, the distribution and diversity of particles in the sampling process are improved through the mutation operation. The defect of particle filter (PF) algorithm where the particles are poor and the utilization rate is not high is also solved. The mutation control function makes the particle set optimization process happen in the early and late stages, and improves the convergence speed of the particle set, which greatly reduces the running time of the whole algorithm. Simulation experiments show that compared with PF and PSO-PF algorithms, the proposed NPSO-PF algorithm has lower root mean square error, shorter running time, higher signal-to-noise ratio and more stable filtering performance. It is proved that the algorithm is suitable for real-time filtering and noise reduction processing of nonlinear signals.

scholarly journals Path planning of lunar robot based on dynamic adaptive ant colony algorithm and obstacle avoidance

2020 ◽  
Vol 17 (3) ◽  
pp. 172988141989897 ◽  
Author(s):  
Shinan Zhu ◽  
Weiyi Zhu ◽  
Xueqin Zhang ◽  
Tao Cao
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Ant Colony Algorithm ◽  
Global Search ◽  
Convergence Speed ◽  
Ant Colony ◽  
Local Optimum ◽  
Adaptive Potential ◽  
Avoidance Strategy

Path planning of lunar robots is the guarantee that lunar robots can complete tasks safely and accurately. Aiming at the shortest path and the least energy consumption, an adaptive potential field ant colony algorithm suitable for path planning of lunar robot is proposed to solve the problems of slow convergence speed and easy to fall into local optimum of ant colony algorithm. This algorithm combines the artificial potential field method with ant colony algorithm, introduces the inducement heuristic factor, and adjusts the state transition rule of the ant colony algorithm dynamically, so that the algorithm has higher global search ability and faster convergence speed. After getting the planned path, a dynamic obstacle avoidance strategy is designed according to the predictable and unpredictable obstacles. Especially a geometric method based on moving route is used to detect the unpredictable obstacles and realize the avoidance of dynamic obstacles. The experimental results show that the improved adaptive potential field ant colony algorithm has higher global search ability and faster convergence speed. The designed obstacle avoidance strategy can effectively judge whether there will be collision and take obstacle avoidance measures.

scholarly journals Parameterized Analysis of Multiobjective Evolutionary Algorithms and the Weighted Vertex Cover Problem

2019 ◽  
Vol 27 (4) ◽  
pp. 559-575
Author(s):  
Mojgan Pourhassan ◽  
Feng Shi ◽  
Frank Neumann
Keyword(s):  
Evolutionary Algorithm ◽  
Complexity Analysis ◽  
Minimum Weight ◽  
Vertex Cover ◽  
Optimal Solution ◽  
Population Based ◽  
Mutation Operator ◽  
Vertex Cover Problem ◽  
Weighted Vertex ◽  
Cover Problem

Evolutionary multiobjective optimization for the classical vertex cover problem has been analysed in Kratsch and Neumann ( 2013 ) in the context of parameterized complexity analysis. This article extends the analysis to the weighted vertex cover problem in which integer weights are assigned to the vertices and the goal is to find a vertex cover of minimum weight. Using an alternative mutation operator introduced in Kratsch and Neumann ( 2013 ), we provide a fixed parameter evolutionary algorithm with respect to [Formula: see text], the cost of an optimal solution for the problem. Moreover, we present a multiobjective evolutionary algorithm with standard mutation operator that keeps the population size in a polynomial order by means of a proper diversity mechanism, and therefore, manages to find a 2-approximation in expected polynomial time. We also introduce a population-based evolutionary algorithm which finds a [Formula: see text]-approximation in expected time [Formula: see text].

scholarly journals COPING WITH COMPLEXITY AND TURBULENCE - AN ENTREPRENEURIAL SOLUTION

2006 ◽  
Vol 14 (04) ◽  
pp. 241-266 ◽  
Author(s):  
ROGER B. MASON
Keyword(s):  
Chaos Theory ◽  
Entrepreneurial Orientation ◽  
Theoretical Underpinning ◽  
Turbulent Environment ◽  
Considerable Similarity ◽  
Turbulent Environments ◽  
Management Approaches ◽  
The Relationship ◽  
A Company

This paper considers the adoption of an entrepreneurial orientation as a paradigm for companies operating in a complex and turbulent environment, viewing the environment as a complex and turbulent system in terms of chaos theory. Approaches suggested by chaos theory are compared with the entrepreneurial orientation to identify if such an orientation matches these suggested approaches. Literature on chaos theory and entrepreneurship is compared, and a short case is presented, providing an illustration of how a company operating successfully in a complex and turbulent environment has used the principles of an entrepreneurial orientation. The paper identifies considerable similarity between the management approaches suggested by chaos theory and the principles of the entrepreneurial orientation, indicating that chaos theory may provide the theoretical underpinning of the relationship between entrepreneurial orientation and turbulent environments. The case also shows how an entrepreneurial orientation has been successfully used in a complex and turbulent environment. The conclusion is that companies operating in a complex and turbulent environment could benefit from adopting an entrepreneurial orientation.

Quantum Evolutionary Algorithm for Chemical Batch Scheduling Problem

2014 ◽  
Vol 1037 ◽  
pp. 506-509
Author(s):  
Qi Tang ◽  
Peng Liu ◽  
Jian Xun Tang
Keyword(s):  
Evolutionary Algorithm ◽  
Time Span ◽  
Scheduling Problem ◽  
Computational Results ◽  
Swarm Optimization ◽  
Short Run ◽  
Feasible Solutions ◽  
Separation Strategy ◽  
Relationship Of ◽  
The Relationship

This paper presents an improved particle swarm optimization combined with quantum evolutionary algorithm (QAE). In the algorithm, continuous coding represents weight information of the batches’ sequence to enhance the ability of handling the constraints. The batch separation strategy unifies the relationship of scheduling time into minimum time span between batches and brings about the feasible processing sequence. Scheduling generation and repair strategies are proposed to obtain feasible solutions. In order to verify the performance of the QAE algorithm, the well-know benchmark scheduling instances are tested. The computational results show that the QAE may find optimal or suboptimal solutions in a short run time for all the instances.

The relationship of delay of gratification and time comprehension in 4-year-old children

2017 ◽  
Vol 42 (4) ◽  
pp. 434-438 ◽  
Author(s):  
Norbert Zmyj
Keyword(s):  
Delay Of Gratification ◽  
Receptive Language ◽  
Language Ability ◽  
Chance Level ◽  
Running Time ◽  
Comprehension Task ◽  
Prepotent Response ◽  
Relationship Of ◽  
To Receive ◽  
The Relationship

In a typical delay-of-gratification task, children have the choice between eating a small amount of treats immediately and waiting in order to receive a larger number of treats. To date, it has not been investigated whether children’s time comprehension is related to the ability to wait for the larger number of treats. Time comprehension can be tested by presenting children with three hourglasses containing different amounts of sand and asking them about the running time of the hourglasses (e.g., “Which hourglass will finish first?”). In this study, 75 four-year-old children were tested with a delay-of-gratification task, a time comprehension task, and a receptive language task. Children who ate the treat immediately in the delay-of-gratification task did not perform above chance level in the time comprehension task. In contrast, children who waited in the delay-of-gratification task, either for some time or until the end of the task, did perform above chance level. Correlation analyses revealed that performance in the time comprehension task and in the delay-of-gratification task correlated even after controlling for receptive language ability. Thus, children’s time comprehension is related to their ability to delay a prepotent response. The nature of this correlation is discussed.

scholarly journals An Effective Hybrid Firefly Algorithm with Harmony Search for Global Numerical Optimization

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Lihong Guo ◽  
Gai-Ge Wang ◽  
Heqi Wang ◽  
Dinan Wang
Keyword(s):  
Numerical Optimization ◽  
Firefly Algorithm ◽  
Harmony Search ◽  
Optimization Methods ◽  
Convergence Speed ◽  
Function Optimization ◽  
Global Numerical Optimization ◽  
Running Time ◽  
Hybrid Metaheuristic ◽  
Better Than

A hybrid metaheuristic approach by hybridizing harmony search (HS) and firefly algorithm (FA), namely, HS/FA, is proposed to solve function optimization. In HS/FA, the exploration of HS and the exploitation of FA are fully exerted, so HS/FA has a faster convergence speed than HS and FA. Also, top fireflies scheme is introduced to reduce running time, and HS is utilized to mutate between fireflies when updating fireflies. The HS/FA method is verified by various benchmarks. From the experiments, the implementation of HS/FA is better than the standard FA and other eight optimization methods.

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