The reptile search algorithm is a newly developed optimization technique that can efficiently solve various optimization problems. However, while solving high-dimensional nonconvex optimization problems, the reptile search algorithm retains some draw...
Recently, various metaheuristic (MH) optimization algorithms have been presented and applied to solve complex engineering and optimization problems. One main category of MH algorithms is the naturally inspired swarm intelligence (SI) algorithms. SI m...
The reptile search algorithm is an effective optimization method based on the natural laws of the biological world. By restoring and simulating the hunting process of reptiles, good optimization results can be achieved. However, due to the limitation...
In this paper, we propose a reptile search algorithm based on Lévy flight and interactive crossover strategy (LICRSA), and the improved algorithm is employed to improve the problems of poor convergence accuracy and slow iteration speed of the...
Data clustering is a complex data mining problem that clusters a massive amount of data objects into a predefined number of clusters; in other words, it finds symmetric and asymmetric objects. Various optimization methods have been used to solve diff...
The telecommunications industry is greatly concerned about customer churn due to dissatisfaction with service. This industry has started investing in the development of machine learning (ML) models for churn prediction to extract, examine and visuali...
Multi-threshold image segmentation is a common technique in computer vision and image analysis. However, segmentation quality suffers greatly as the number of thresholds increases, particularly for color image segmentation tasks. To address this chal...
In the realm of computational problem-solving, the search for efficient algorithms tailored for real-world engineering challenges and software requirement prioritization is relentless. This paper introduces the Multi-Learning-Based Reptile Search Alg...
Solar systems connected to the grid are crucial in addressing the global energy crisis and meeting rising energy demand. The efficiency of these systems is totally impacted by varying weather conditions such as changes in irradiance and temperature t...
Feature Selection (FS) is a major preprocessing stage which aims to improve Machine Learning (ML) models’ performance by choosing salient features, while reducing the computational cost. Several approaches are presented to select the most Optim...
Multiple-Object Tracking (MOT) has become more popular because of its commercial and academic potential. Though various techniques were devised for managing this issue, it becomes a challenge because of factors such as severe object occlusions and ab...
This paper proposed a short-term two-stage hybrid algorithmic framework for trade and trend analysis of the Forex market by augmenting the currency pair datasets with transformed attributes using a few technical indicators and statistical measures. I...
This paper addresses the critical security challenges in the internet of things (IoT) landscape by implementing an innovative solution that combines convolutional neural networks (CNNs) for feature extraction and the XGBoost model for intrusion detec...
Precise estimation of water temperature plays a key role in environmental impact assessment, aquatic ecosystems’ management and water resources planning and management. In the current study, convolutional neural networks (CNN) and long short-te...
The multilevel inverters (MLIs) are capable of handling large quantities of power and generating high-quality output voltages. Consequently, the size of the filters is reduced, and the circuitry is simplified. As a result, they have a diverse range o...
The seepage characteristics of clay core walls are crucial for the seepage safety of core rockfill dams, with the permeability coefficient in the unsaturated zone being nonlinear. To accurately determine the unsaturated seepage parameters in clay cor...
Binarizing continuous metaheuristics to solve challenging NP-hard binary optimization problems is a fundamental step in adapting continuous algorithms for discrete domains. Binary optimization problems, such as the Set Covering Problem and the 0&ndas...
This research is aimed to escalate Adaptive Neuro-Fuzzy Inference System (ANFIS) functioning in order to ensure the veracity of existing time-series modeling. The COVID-19 pandemic has been a global threat for the past three years. Therefore, advance...
The utilization of gene selection techniques is crucial when dealing with extensive datasets containing limited cases and numerous genes, as they enhance the learning processes and improve overall outcomes. In this research, we introduce a hybrid met...
Dried Hami jujube has great commercial and nutritional value. Starch-head and mildewed fruit are defective jujubes that pose a threat to consumer health. A novel method for detecting starch-head and mildewed fruit in dried Hami jujubes with visible/n...
This paper presents a deformation prediction model for concrete dams that integrates a reptile search algorithm (RSA), a Variational Mode Decomposition (VMD) algorithm, and a long short-term memory network model with attention mechanism (AttLSTM). Th...
The combination of rice husk ash and common concrete both reduces carbon dioxide emission and solves the problem of agricultural waste disposal. However, the measurement of the compressive strength of rice husk ash concrete has become a new challenge...
Dam displacement monitoring is crucial for assessing structural safety; however, conventional models often prioritize single-task prediction, leading to an inherent difficulty in balancing monitoring data quality with model performance. To bridge thi...
This study presents an innovative home energy management system (HEMS) that incorporates PV, WTs, and hybrid backup storage systems, including a hydrogen storage system (HSS), a battery energy storage system (BESS), and electric vehicles (EVs) with v...
The swelling potentiality is a vital property of fine-grained soils strictly related to the index properties and chemical composition. The integration of machine learning techniques and geotechnical parameters provided a new integrative approach for...
Background: Attention-Deficit/Hyperactivity Disorder (ADHD) represents a widely prevalent and heterogeneous neurodevelopmental condition in pediatric populations, often exhibiting a substantial propensity to persist into adulthood. ADHD is a multifac...
In this study, the authors demonstrate the development and evaluation of an optimal frequency control controller for an interlinked two-area power system that incorporates Renewable Energy Sources (RESs). In decentralized power grids, the Load Freque...
Bio-inspired swarm metaheuristic algorithms constitute a widely used tool for solving complex optimization problems. However, the experimental characterization of their emergent behavior remains a methodological challenge. This study proposes an expe...
Nature-inspired metaheuristic algorithms have gained great attention over the last decade due to their potential for finding optimal solutions to different optimization problems. In this study, a metaheuristic based on the dwarf mongoose optimization...
The Planet Optimization Algorithm (POA) is a meta-heuristic inspired by celestial mechanics, drawing on Newtonian gravitational principles to simulate planetary dynamics in optimization search spaces. While the POA demonstrates a strong performance i...
In the past decade, artificial neural networks (ANNs) have been widely employed to address many problems. Despite their powerful problem-solving capabilities, ANNs are susceptible to a significant risk of stagnation in local minima due to using backp...
Swarm-based metaheuristics have shown significant progress in solving different complex optimization problems, including the parameter identification of linear, as well as nonlinear, systems. Nonlinear systems are inherently stiff and difficult to op...
Unmanned Aerial Vehicles (UAVs) are increasingly utilized for urban patrol and defense owing to their low cost, high mobility, and rapid deployment. This paper proposes a multi-UAV mission planning model that takes into account mission execution rate...
Skin Cancer (SC) is among the most hazardous due to its high mortality rate. Therefore, early detection of this disease would be very helpful in the treatment process. Multilevel Thresholding (MLT) is widely used for extracting regions of interest fr...
This paper introduces a novel physical-inspired metaheuristic algorithm called “Light Spectrum Optimizer (LSO)” for continuous optimization problems. The inspiration for the proposed algorithm is the light dispersions with different angle...
The purpose of this paper is to address an urgent operational issue referring to optimal power flow (OPF), which is associated with a number of technical and financial aspects relating to issues of environmental concern. In the last few decades, OPF...
Background: In our current digital world, smartphones are no longer limited to communication but are used in various real-world applications. In the healthcare industry, smartphones have sensors that can record data about our daily activities. Such d...
This paper proposes a dual-channel network of a sustainable Closed-Loop Supply Chain (CLSC) for rice considering energy sources and consumption tax. A Mixed Integer Linear Programming (MILP) model is formulated for optimizing the total cost, the amou...
As solar energy generation has become more and more important for the economies of numerous countries in the last couple of decades, it is highly important to build accurate models for forecasting the amount of green energy that will be produced. Num...
Frequency regulation (FR) constitutes a fundamental aspect of power system stability, particularly in the context of the growing integration of intermittent renewable energy sources (RES) and electric vehicles (EVs). The load frequency control (LFC)...
Data sharing with additional devices across wireless networks is made simple and advantageous by the Internet of Things (IoT), an emerging technology. However, IoT systems are more susceptible to cyberattacks because of their continued growth and tec...
Preston’s equation is a general model describing the egg shape of birds. The parameters of Preston’s equation are usually estimated after re-expressing it as the Todd-Smart equation and scaling the egg’s actual length to two. This m...