Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
Data clustering and classification have become indispensable for extracting actionable insights from large-scale, heterogeneous datasets characterised by high volume, velocity and variety. Clustering ...
This article exclusively formulates and presents three innovative hypotheses related to the execution of share buybacks, employing Genetic Algorithms (GAs) and mathematical optimization techniques.
Abstract: Traditional particle swarm optimization algorithms (PSO) targeted to solve large scale problems are mostly serial, such as CCPSO2, and the computing time is very long in general. Therefore, ...
Abstract: The algorithm for feature selection using multi- objective particle swarm optimization has been effectively implemented in certain programs. Existing algorithms face difficulties in handling ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The rate of penetration (ROP) is a manifestation of drilling efficiency, and ...
This study proposes a new superior hybrid algorithm, which is the particle swarm optimization (PSO) and gene algorithm (GA)-based neural network to predict the leakage current of insulators. The ...
In view of the difficulty of applying the refine modeling of combined heat and power (CHP) units to the optimization scenario of integrated energy system, a CHP unit model based on working point ...
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