scholarly journals A Novel Mating Approach for Genetic Algorithms

2013 ◽  
Vol 21 (2) ◽  
pp. 197-229 ◽  
Author(s):  
Severino F. Galán ◽  
Ole J. Mengshoel ◽  
Rafael Pinter
Keyword(s):  
Genetic Algorithms ◽  
Random Mating ◽  
Adaptive Strategy ◽  
Mating Strategies ◽  
Function Optimization ◽  
The Novel ◽  
Independent Manner ◽  
Novel Approach ◽  
Domain Independent ◽  
Self Adaptive

Genetic algorithms typically use crossover, which relies on mating a set of selected parents. As part of crossover, random mating is often carried out. A novel approach to parent mating is presented in this work. Our novel approach can be applied in combination with a traditional similarity-based criterion to measure distance between individuals or with a fitness-based criterion. We introduce a parameter called the mating index that allows different mating strategies to be developed within a uniform framework: an exploitative strategy called best-first, an explorative strategy called best-last, and an adaptive strategy called self-adaptive. Self-adaptive mating is defined in the context of the novel algorithm, and aims to achieve a balance between exploitation and exploration in a domain-independent manner. The present work formally defines the novel mating approach, analyzes its behavior, and conducts an extensive experimental study to quantitatively determine its benefits. In the domain of real function optimization, the experiments show that, as the degree of multimodality of the function at hand grows, increasing the mating index improves performance. In the case of the self-adaptive mating strategy, the experiments give strong results for several case studies.

scholarly journals Self-Adaptive Genetic Algorithms with Simulated Binary Crossover

2001 ◽  
Vol 9 (2) ◽  
pp. 197-221 ◽  
Author(s):  
Kalyanmoy Deb ◽  
Hans-Georg Beyer
Keyword(s):  
Genetic Algorithms ◽  
Essential Feature ◽  
Function Optimization ◽  
Real Parameter ◽  
The Self ◽  
Test Problems ◽  
Adaptive Genetic Algorithms ◽  
Working Principle ◽  
Self Adaptation ◽  
Self Adaptive

Self-adaptation is an essential feature of natural evolution. However, in the context of function optimization, self-adaptation features of evolutionary search algorithms have been explored mainly with evolution strategy (ES) and evolutionary programming (EP). In this paper, we demonstrate the self-adaptive feature of real-parameter genetic algorithms (GAs) using a simulated binary crossover (SBX) operator and without any mutation operator. The connection between the working of self-adaptive ESs and real-parameter GAs with the SBX operator is also discussed. Thereafter, the self-adaptive behavior of real-parameter GAs is demonstrated on a number of test problems commonly used in the ES literature. The remarkable similarity in the working principle of real-parameter GAs and self-adaptive ESs shown in this study suggests the need for emphasizing further studies on self-adaptive GAs.

Evaluation of side orifices shape factor using the novel approach self-adaptive extreme learning machine

2019 ◽  
Vol 5 (3) ◽  
pp. 925-935
Author(s):  
Ali Reza Mahmodian ◽  
Ahmad Rajabi ◽  
Mohammad Ali Izadbakhsh ◽  
Saeid Shabanlou
Keyword(s):  
Extreme Learning Machine ◽  
Shape Factor ◽  
The Novel ◽  
Novel Approach ◽  
Learning Machine ◽  
Self Adaptive

The novel approach for optical proximity correction using genetic algorithms

2005 ◽  
Author(s):  
Tetsuaki Matsunawa ◽  
Hirokazu Nosato ◽  
Hidenori Sakanashi ◽  
Masahiro Murakawa ◽  
Nobuharu Murata ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
The Novel ◽  
Optical Proximity Correction ◽  
Novel Approach

Exploring normative perceptions and misperceptions of private, environmentally impactful behaviours

2020 ◽  
Author(s):  
Elaine Gallagher ◽  
Bas Verplanken ◽  
Ian Walker
Keyword(s):  
Social Norms ◽  
Behaviour Change ◽  
Social Contexts ◽  
The Novel ◽  
Normative Influence ◽  
Change Mechanism ◽  
Novel Approach ◽  
Classical Studies ◽  
Referent Group

Social norms have been shown to be an effective behaviour change mechanism across diverse behaviours, demonstrated from classical studies to more recent behaviour change research. Much of this research has focused on environmentally impactful actions. Social norms are typically utilised for behaviour change in social contexts, which facilitates the important element of the behaviour being visible to the referent group. This ensures that behaviours can be learned through observation and that deviations from the acceptable behaviour can be easily sanctioned or approved by the referent group. There has been little focus on how effective social norms are in private or non-social contexts, despite a multitude of environmentally impactful behaviours occurring in the home, for example. The current study took the novel approach to explore if private behaviours are important in the context of normative influence, and if the lack of a referent groups results in inaccurate normative perceptions and misguided behaviours. Findings demonstrated variance in normative perceptions of private behaviours, and that these misperceptions may influence behaviour. These behaviours are deemed to be more environmentally harmful, and respondents are less comfortable with these behaviours being visible to others, than non-private behaviours. The research reveals the importance of focusing on private behaviours, which have been largely overlooked in the normative influence literature.

Weight modification accumulated epochs RAIM algorithm based on self-adaptive strategy

2013 ◽  
Vol 33 (8) ◽  
pp. 2366-2369
Author(s):  
Guorong HUANG ◽  
Cheng CHANG ◽  
Shunyi HAO ◽  
Yanan CHANG ◽  
Gang XU
Keyword(s):  
Adaptive Strategy ◽  
Self Adaptive

scholarly journals A Novel Approach to EEG Speech Activity Detection with Visual Stimuli and Mobile BCI

2021 ◽  
Vol 11 (2) ◽  
pp. 674
Author(s):  
Marianna Koctúrová ◽  
Jozef Juhár
Keyword(s):  
Visual Stimuli ◽  
Computer Interface ◽  
Single Subject ◽  
Detection Accuracy ◽  
The Novel ◽  
Activity Detection ◽  
Speech Activity ◽  
Novel Approach ◽  
Eeg Data ◽  
Speech Activity Detection

With the ever-progressing development in the field of computational and analytical science the last decade has seen a big improvement in the accuracy of electroencephalography (EEG) technology. Studies try to examine possibilities to use high dimensional EEG data as a source for Brain to Computer Interface. Applications of EEG Brain to computer interface vary from emotion recognition, simple computer/device control, speech recognition up to Intelligent Prosthesis. Our research presented in this paper was focused on the study of the problematic speech activity detection using EEG data. The novel approach used in this research involved the use visual stimuli, such as reading and colour naming, and signals of speech activity detectable by EEG technology. Our proposed solution is based on a shallow Feed-Forward Artificial Neural Network with only 100 hidden neurons. Standard features such as signal energy, standard deviation, RMS, skewness, kurtosis were calculated from the original signal from 16 EEG electrodes. The novel approach in the field of Brain to computer interface applications was utilised to calculated additional set of features from the minimum phase signal. Our experimental results demonstrated F1 score of 86.80% and 83.69% speech detection accuracy based on the analysis of EEG signal from single subject and cross-subject models respectively. The importance of these results lies in the novel utilisation of the mobile device to record the nerve signals which can serve as the stepping stone for the transfer of Brain to computer interface technology from technology from a controlled environment to the real-life conditions.

ChemInform Abstract: The Novel Approach to Indole Alkaloids by Using Pd(II)-Catalyzed Cyclization.

ChemInform ◽  
2015 ◽  
Vol 46 (17) ◽  
pp. no-no
Author(s):  
Hajime Yokoyama ◽  
Takayoshi Kubo ◽  
Yosuke Matsumura ◽  
Junichi Hosokawa ◽  
Masahiro Miyazawa ◽  
...  
Keyword(s):  
Indole Alkaloids ◽  
The Novel ◽  
Novel Approach

scholarly journals Caffeine-Induced Effects on Human Skeletal Muscle Contraction Time and Maximal Displacement Measured by Tensiomyography

Nutrients ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 815
Author(s):  
Przemysław Domaszewski ◽  
Paweł Pakosz ◽  
Mariusz Konieczny ◽  
Dawid Bączkowicz ◽  
Ewa Sadowska-Krępa
Keyword(s):  
Skeletal Muscle ◽  
Muscle Activation ◽  
Electric Pulse ◽  
Professional Athletes ◽  
Mechanical Activity ◽  
The Novel ◽  
Contraction Time ◽  
Novel Approach ◽  
Skeletal Muscle Contraction ◽  
Maximal Displacement

Studies on muscle activation time in sport after caffeine supplementation confirmed the effectiveness of caffeine. The novel approach was to determine whether a dose of 9 mg/kg/ body mass (b.m.) of caffeine affects the changes of contraction time and the displacement of electrically stimulated muscle (gastrocnemius medialis) in professional athletes who regularly consume products rich in caffeine and do not comply with the caffeine discontinuation period requirements. The study included 40 professional male handball players (age = 23.13 ± 3.51, b.m. = 93.51 ± 15.70 kg, height 191 ± 7.72, BMI = 25.89 ± 3.10). The analysis showed that in the experimental group the values of examined parameters were significantly reduced (p ≤ 0.001) (contraction time: before = 20.60 ± 2.58 ms/ after = 18.43 ± 3.05 ms; maximal displacement: before = 2.32 ± 0.80 mm/after = 1.69 ± 0.51 mm). No significant changes were found in the placebo group. The main achievement of this research was to demonstrate that caffeine at a dose of 9 mg/kg in professional athletes who regularly consume products rich in caffeine has a direct positive effect on the mechanical activity of skeletal muscle stimulated by an electric pulse.

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