Identifying the underlying factors derived from geospatial and remote sensing data that contribute to forest fires is of paramount importance. It aids experts in pinpointing areas and periods most susceptible to these incidents. In this study, we emp...
Nature-inspired metaheuristic algorithms are commonly applied to complex combinatorial optimization problems where exact methods are computationally impractical. Tourist route optimization is a representative multi-objective problem characterized by...
Activated sludge models (ASMs) are often used in the simulation of the wastewater treatment process to evaluate whether the effluent quality parameters of a wastewater treatment plant meet the standards. The premise of successful simulation is to cho...
One of the effectual text classification approaches for learning extensive information is incremental learning. The big issue that occurs is enhancing the accuracy, as the text is comprised of a large number of terms. In order to address this issue,...
Reservoir optimal operation considering aquatic ecological protection is a hot topic in current research. This paper proposes an improved minimum monthly average runoff method (IMMR) for calculating environmental flow and an improved invasive weed op...
Reservoir operation under climate change poses significant challenges for hydropower-dependent countries, particularly in cascade reservoir systems. This study aims to derive optimal future operating rule curves for the Nam Khan 2 and Nam Khan 3 casc...
In this paper, an optimal design of a microgrid including four houses in Dakhla city (Morocco) is proposed. To make this study comprehensive and applicable to any hybrid system, each house has a different configuration of renewable energies. The conf...
Fault diagnosis of induction motor anomalies is vital for achieving industry safety. This paper proposes a new hybrid Machine Learning methodology for induction-motor fault detection. Some of the motor parameters such as the stator currents and vibra...
The significance of accurate heating load (HL) approximation is the primary motivation of this research to distinguish the most efficient predictive model among several neural-metaheuristic models. The proposed models are formulated through synthesiz...
This study presents three new hybrid artificial intelligence optimization models—namely, adaptive neuro-fuzzy inference system (ANFIS) with cultural (ANFIS-CA), bees (ANFIS-BA), and invasive weed optimization (ANFIS-IWO) algorithms—for flood suscepti...
Due to the increasing complexity of industrial systems, fault detection hinders the continuity of productivity. Also, many methods in industrial systems whose complexity increases over time have a mechanism based on human intervention. Therefore, the...
We propose an improved DNN modeling method based on two optimization algorithms, namely the linear decreasing weight particle swarm optimization (LDWPSO) algorithm and invasive weed optimization (IWO) algorithm, for predicting vehicle’s longitu...
Wireless sensor networks (WSNs) is a multi-hop wireless network composed of a group of static or mobile sensor nodes in the form of self-organization. Uneven distribution of nodes often leads to the problem of over coverage and incomplete coverage of...
This paper presents the application of three optimization algorithms to increase the chaotic behavior of the fractional order chaotic Chen system. This is achieved by optimizing the maximum Lyapunov exponent (MLE). The applied optimization techniques...
Weed invasion of crop fields, such as maize, is a major threat leading to yield reductions or crop right-offs for smallholder farming, especially in developing countries. A synoptic view and timeous detection of weed invasions can save the crop. The...
The study proposed a robotic calibration algorithm for improving the robot manipulator position precision. At first, the kinematic parameters as well as the compliance parameters of the robot can be identified together to improve its accuracy using t...
This article proposes a novel damage detection method based on the sensitivity analysis and chaotic moth-flame-invasive weed optimization (CMF-IWO), which is utilized to simultaneously identify the damage of structural elements and bearings. First, t...
The Tree-based Pipeline Optimization Tool (TPOT) is a state-of-the-art automated machine learning (AutoML) approach that automatically generates and optimizes tree-based pipelines using a genetic algorithm. Although it has been proven to outperform c...
Nowadays, the high-dimensionality of data causes a variety of problems in machine learning. It is necessary to reduce the feature number by selecting only the most relevant of them. Different approaches called Feature Selection are used for this task...
Weeds are unwanted and invasive plants characterized by their rapid growth and ability to compete with crops for essential resources such as space, water, nutrients, and sunlight. This competition has a negative impact on crop quality and productivit...
Recently, fast uptake of renewable energy sources (RES) in the world has introduced new difficulties and challenges; one of the most important challenges is providing economic energy with high efficiency and good quality. To reach this goal, many tra...
In optimization algorithms, there are some challenges, including lack of optimal solution, slow convergence, lack of scalability, partial search space, and high computational demand. Inspired by the process of gold exploration and exploitation, we pr...
In the recent past, the volume of spatial datasets has significantly increased. This is attributed to, among other factors, higher sensor temporal resolutions of the recently launched satellites. The increased data, combined with the computation and...
To enhance the efficiency of solving the optimal operation model for cascade reservoirs, this paper first constructed an optimal operation model of cascade reservoirs. The model comprehensively considered the ecological flow, the guaranteed output of...
This paper focuses on the prediction of soil shear strength (SSS), which is one of the most fundamental parameters in geotechnical engineering. Consisting of 12 influential factors, namely depth of sample, percentage of sand, percentage of loam, perc...
The main goal of this work is to optimize the chaotic behavior of a three-dimensional chaotic-spherical-attractor-generating fractional-order system and compare the results with its novel hyperchaotic counterpart. The fractional-order chaotic system...
Considering the scouring depth downstream of weirs is a challenging issue due to its effect on weir stability. The adaptive neuro-fuzzy inference systems (ANFIS) model integrated with optimization methods namely cultural algorithm, biogeography based...
Stellera chamaejasme (Thymelaeaceae) is amongst the worst invasive species of the alpine grasslands on the Qinghai–Tibet Plateau; timely and effective monitoring is critical for its prevention and control. In this study, by using high spatial r...
Lung cancer is a prevalent malignancy that impacts individuals of all genders and is often diagnosed late due to delayed symptoms. To catch it early, researchers are developing algorithms to study lung cancer images. The primary objective of this wor...
Concrete filled steel tubes (CFSTs) show advantageous applications in the field of construction, especially for a high axial load capacity. The challenge in using such structure lies in the selection of many parameters constituting CFST, which necess...
This study explores the feasibility of using portable near-infrared spectroscopy for the rapid and non-destructive detection of coffee adulteration. Spectral data from adulterated coffee samples in the 900–1700 nm range were collected and proce...
A significant growth in PV (photovoltaic) system installations have been observed during the last decade. The PV array has a nonlinear output characteristic because of weather intermittency. Partial shading is an environmental phenomenon that causes...
With the continuous increase in motor vehicle ownership in recent times, traditional transportation has been unable to meet people’s travel needs. Research on autonomous driving technology will help solve a series of problems associated with dr...
This paper addresses the protection coordination problem of microgrids combining unsupervised learning techniques, metaheuristic optimization and non-standard characteristics of directional over-current relays (DOCRs). Microgrids may operate under di...
The adoption and recent development of Unmanned Aerial Vehicles (UAVs) are because of their widespread applications in the private and public sectors, from logistics to environment monitoring. The incorporation of 5G technologies, satellites, and UAV...
Website phishing is a cyberattack that targets online users for stealing their sensitive data containing login credential and banking details. The phishing websites appear very similar to their equivalent legitimate websites for attracting a huge amo...
In struggling against invasive species ravaging riverscape ecosystems, gaps in dispersal pathway knowledge and fragmented approaches across scales have long stalled effective riparian management worldwide. To reduce these limitations and enhance inva...
Gantry-type dual-axis platforms can be used to move heavy loads or perform precision CNC work. Such gantry systems drive a single axis with two linear motors, and under heavy loads, a high driving force is required. This can generate a pulling force...
The groundwater contained in aquifers is among the most important water supply resources, especially in semi-arid and arid regions worldwide. This study aims to evaluate and compare the prediction capability of two well–known models, support ve...
Proper irrigation scheduling and agricultural water management require a precise estimation of crop water requirement. In practice, reference evapotranspiration (ETo) is firstly estimated, and used further to calculate the evapotranspiration of each...
In order to improve maximum power point tracking (MPPT) and energy extraction in grid-connected photovoltaic (PV) systems under various climatic conditions, this research proposes a Secretary Bird Optimization-tuned Super-Twisting Sliding Mode Contro...
In many site investigation phases of civil and mining engineering projects, the tensile strength of the rocks is one of the most significant parameters that must be identified. This parameter can be determined directly through laboratory tests. Howev...
Fresh water lakes are vulnerable assets that need to be protected against manmade/natural challenges like climate change and anthropogenesis activities. This study addresses the predictability of the lake water level changes based on the knowledge ac...
Remotely sensed cropland abandonment monitoring is crucial for providing spatially explicit references for maintaining sustainable agricultural practices and ensuring food security. However, abandoned cropland is commonly detected based on multi-date...
Discrete-Variable Quantum Key Distribution (DV-QKD) provides a mechanism for establishing secret keys between legitimate parties using quantum-state transmission and authenticated classical post-processing. In this work, the underlying quantum layer...