Nonconvexity is a usually overlooked factor in economic dispatch (ED). Enhancing the nonconvexity of the objective function leads traditional convex optimization algorithms easily to fall into the ...

Moreover, a hierarchy of discrete attention is devised to further improve the effectiveness, which develops our method into the mature one, hierarchically attentioned binary-search-based LSH (HA-BLSH) ...

High dimensionality often challenges the efficiency and accuracy of a classifier, while evolutionary feature selection is an effective method for data preprocessing and dimensionality reduction.

Abstract—The effective identification of binary cryptographic algorithms provides crucial technical support for encryption cracking and security mechanism analysis. However, the identification of ...

In this paper, a bi-dimensional search method is proposed for unconstrained optimization problems. Traditional methods for solving the unconstrained optimization problems are usually based on ...

Efficiently finding similar items in large datasets is a crucial task with applications in various domains. This abstract presents a survey of algorithms and techniques designed for this purpose.

Presents corrections to the paper, (Corrections to “MOBCSA: Multi-Objective Binary Cuckoo Search Algorithm for Features Selection in Bioinformatics”).

This paper proposes a new Binary Crayfish Optimization Algorithm (BinCOA) for feature selection. The Crayfish Optimization Algorithm (COA) is a new metaheuristic algorithm inspired by the simulation ...

Binary search algorithms are categorized as algorithms based on the trie structure, algorithms performing binary search on prefix values, and algorithms performing binary search on prefix lengths. In ...

In this paper, described depth first search algorithm being implemented on line maze solver robot. Right hand rule will be used to select the turn priority. Some mazes will be used to test the ...

Machine Learning (ML) has become a vast umbrella of various algorithms. Certainly, even for classification models, there are numerous algorithms such as Logistic Regression, Naïve Bayes Classifier, ...