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Genetic algorithms: Theory, genetic operators, solutions, and applications
A genetic algorithm (GA) is an evolutionary algorithm inspired by the natural selection and
biological processes of reproduction of the fittest individual. GA is one of the most popular …
biological processes of reproduction of the fittest individual. GA is one of the most popular …
[HTML][HTML] Choosing mutation and crossover ratios for genetic algorithms—a review with a new dynamic approach
Genetic algorithm (GA) is an artificial intelligence search method that uses the process of
evolution and natural selection theory and is under the umbrella of evolutionary computing …
evolution and natural selection theory and is under the umbrella of evolutionary computing …
A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge
Discovering a meaningful symbolic expression that explains experimental data is a
fundamental challenge in many scientific fields. We present a novel, open-source …
fundamental challenge in many scientific fields. We present a novel, open-source …
Optimized extreme learning machine for detecting DDoS attacks in cloud computing
Distributed denial of service (DDoS) attack is a serious security threat to cloud computing
that affects the availability of cloud services. Therefore, defending against these attacks …
that affects the availability of cloud services. Therefore, defending against these attacks …
Biphase adaptive learning-based neural network model for cloud datacenter workload forecasting
Cloud computing promises elasticity, flexibility and cost-effectiveness to satisfy service level
agreement conditions. The cloud service providers should plan and provision the computing …
agreement conditions. The cloud service providers should plan and provision the computing …
An ensemble method to improve prediction of earthquake-induced soil liquefaction: a multi-dataset study
Abstract Evaluation of earthquake-induced liquefaction potential is crucial in the design
phase of construction projects. Although several machine learning models achieve good …
phase of construction projects. Although several machine learning models achieve good …
[HTML][HTML] Benchmarking biologically-inspired automatic machine learning for economic tasks
Data-driven economic tasks have gained significant attention in economics, allowing
researchers and policymakers to make better decisions and design efficient policies …
researchers and policymakers to make better decisions and design efficient policies …
Applying genetic algorithm and ant colony optimization algorithm into marine investigation path planning model
Y Liang, L Wang - Soft Computing, 2020 - Springer
Marine resources are vital to the development of a country. Marine investigation can obtain
more marine resources and acquire more marine environmental information. A common …
more marine resources and acquire more marine environmental information. A common …
An Efficiency Boost for Genetic Algorithms: Initializing the GA with the Iterative Approximate Method for Optimizing the Traveling Salesman Problem—Experimental …
The genetic algorithm (GA) is a well-known metaheuristic approach for dealing with complex
problems with a wide search space. In genetic algorithms (GAs), the quality of individuals in …
problems with a wide search space. In genetic algorithms (GAs), the quality of individuals in …
An improved genetic algorithm with a new initialization mechanism based on regression techniques
Genetic algorithm (GA) is one of the well-known techniques from the area of evolutionary
computation that plays a significant role in obtaining meaningful solutions to complex …
computation that plays a significant role in obtaining meaningful solutions to complex …