Predicting future stock index price movement has always been a fascinating research area
both for the investors who wish to yield a profit by trading stocks and for the researchers who …

This study aimed to classifying wheat genotypes using support vector machines (SVMs)
improved with ensemble algorithms and optimization techniques. Utilizing data from 302 …

As the largest terrestrial carbon pool, soil organic carbon (SOC) has the potential to
influence and mitigate climate change; thus, SOC monitoring is of high importance in the …

In order to detect adulterants on Lycium Chinense species effectively, a rapid, clean, and
nondestructive detection method based on hyperspectral imaging (HSI) technology was …

Purpose The purpose of this paper is to tune support vector machine (SVM) classifier using
grey wolf optimizer (GWO). Design/methodology/approach The schema of the work aims at …

The plasma membrane of eukaryotic cells is commonly believed to contain ordered lipid
domains. The interest in understanding the origin of such domains has led to extensive …

The classification performance of a weighted voting ensemble of classifiers largely depends
on the proper weight chosen for each base classifier's vote. In this paper, we propose the …

Abstract Machine-learning algorithms are good at computing non-linear problems and fitting
complex composite functions, which makes them an adequate tool for addressing multiple …

The classification performance of support vector machine (SVM) algorithm is highly
dependent on the careful tuning of hyper-parameters and penalty coefficient. This paper …

This paper presents a hybrid classification algorithm, ACOMV-SVM which is based on ant
colony and support vector machine. A new direction for ant colony optimisation is to optimise …