In order to keep the" good" status of coastal water quality, it is essential to monitor and
assess frequently. The Water quality index (WQI) model is one of the most widely used …

Wastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable
and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods …

Abstract Treatment of municipal wastewater to meet the stringent effluent quality standards is
an energy-intensive process and the main contributor to the costs of wastewater treatment …

Improving accuracies of machine learning algorithms is vital in designing high performance
computer-aided diagnosis (CADx) systems. Researches have shown that a base classifier …

This paper presents a new feature selection (FS) algorithm based on the wrapper approach
using neural networks (NNs). The vital aspect of this algorithm is the automatic …

Although there is clinical demand for new technology that can accurately measure
Parkinsonian tremors, automatic scoring of Parkinsonian tremors using machine-learning …

Feature selection becomes a prominent method in the big data era. The logistic regression
model is a wrapper method that provides better classification or prediction accuracy but it is …

Software is the heartbeat of modern day technology. In order to keep up with the pace of
modern day expansion, change in any software is inevitable. Defects and enhancements …

Feature selection is an important data preprocessing step which is performed before a
learning algorithm is applied. The issue that has to be taken into consideration when …

Attribute reduction (AR) represents a NP-hard problem, and it is be identified as the
problematic issue of pinpointing the least (possible) subset of characteristics taken from the …