Swarm-based algorithm can successfully avoid the local optimal constraints, thus achieving a smooth balance between exploration and exploitation. Salp swarm algorithm (SSA), as a swarm-based algorithm on account of the predation behavior of the salp,...
To address the defects of the salp swarm algorithm (SSA) such as the slow convergence speed and ease of falling into a local minimum, a new salp swarm algorithm combining chaotic mapping and decay factor is proposed and combined with back propagation...
The basic Salp Swarm Algorithm (SSA) offers advantages such as a simple structure and few parameters. However, it is prone to falling into local optima and remains inadequate for seed classification tasks that involve hyperparameter optimization of m...
To address uneven population distribution and premature convergence of the standard Salp Swarm Algorithm (SSA) in grid-connected microgrid scheduling, this study develops an Improved Salp Swarm Algorithm (ISSA). Sine chaotic mapping is used for popul...
This paper employs an optimization algorithm called the salp swarm algorithm (SSA) for the parameter estimation of the soil water retention curve model. The SSA simulates the behavior of searching for food of the salp swarm and manages to find the op...
The localization of sensor nodes is an important problem in wireless sensor networks. The DV-Hop algorithm is a typical range-free algorithm, but the localization accuracy is not high. To further improve the localization accuracy, this paper designs...
We live in a period when smart devices gather a large amount of data from a variety of sensors and it is often the case that decisions are taken based on them in a more or less autonomous manner. Still, many of the inputs do not prove to be essential...
The salp swarm algorithm imitates the swarm behavior of salps during navigation and hunting that has been proven the superiority of search for best solution. However, although it has sufficient global search ability, it is still worth paying attentio...
The less-than-truckload (LTL) freight problem is a general pain point in logistics applications. Its challenge resides in the fact that these loads cannot be shipped in a timely manner due to their relatively small volumes. Traditional LTL matching m...
The mast is a critical component of rotary drilling rigs, which has a cross-section consisting of a rectangular shape formed by two web plates and two flange plates. Structural optimization of the mast is necessary to address the issue of excessive w...
In complex two-dimensional monitoring environments, how to enhance network efficiency and network lifespan while utilizing limited energy resources, and ensuring that wireless sensor networks achieve the required partial coverage of the monitoring ar...
In this paper, we introduce a new and advanced multi-feature selection method for bacterial classification that uses the salp swarm algorithm (SSA). We improve the SSA’s performance by using opposition-based learning (OBL) and a local search al...
The article presents an algorithm and optimization software designed for the optimal configuration of a tuned inductive choke. The optimization software consists of two main parts: an optimization procedure and a mathematical model for the designed e...
Target assignment is a core issue in command and control, aiming to rationally distribute targets among multiple coordinated operational units based on battlefield conditions to maximize overall operational effectiveness. This study proposes a target...
The system of nonlinear equations (SNLEs) is one of the eminent problems in science and engineering, and it is still open to research. A new hybrid intelligent algorithm is presented in this research to solve SNLEs. It is a composite of the salp swar...
The efficiency and smoothness of path planning algorithms are critical factors influencing their practical applications. A traditional A* algorithm suffers from limitations in search efficiency, path smoothness, and obstacle avoidance. To address the...
Aiming at the problem of path planning for autonomous underwater vehicle (AUV) to cope with the influence of obstacles and eddies in complex marine environments, a path planning method based on an improved salp swarm algorithm (ISSA) is proposed. Fir...
The high utilization of renewable energy to manage climate change and provide green energy requires short-term photovoltaic (PV) power forecasting. In this paper, a novel forecasting strategy that combines a convolutional neural network (CNN) and a s...
Green scheduling is not only an effective way to achieve green manufacturing but also an effective way for modern manufacturing enterprises to achieve energy conservation and emission reduction. The double-flexible job shop scheduling problem (DFJSP)...
In long-distance gas transmission pipelines, there are many booster compressor stations consisting of parallel compressors that provide pressure for the delivery of natural gas. So, it is economically important to optimize the operation of the booste...
Due to the rising cost of fuel, increased demand for energy, and the stresses of environmental issues, dynamic economic emission dispatch (DEED), which is the most precise mode for actual dispatching conditions, has been a significant study topic in...
In recent times, cybercrime has increased significantly and dramatically. This made the need for Digital Forensics (DF) urgent. The main objective of DF is to keep proof in its original state by identifying, collecting, analyzing, and evaluating digi...
Currently, numerous intelligent maximum power point tracking (MPPT) algorithms are capable of tackling the global optimization challenge of multi-peak photovoltaic output power under partial shading conditions, yet they often face issues such as slow...
Power quality disturbance (PQD) is an influential situation that significantly declines the reliability of electrical distribution systems. Therefore, PQD classification is an important process for preventing system reliability degradation. This pape...
Reasonable optimal operation policy for complex multiple reservoir systems is very important for the safe and efficient utilization of water resources. The operation policy of multiple hydropower reservoirs should be optimized to maximize total hydro...
To provide an available diagnostic model for diagnosing coronary atherosclerotic heart disease to provide an auxiliary function for doctors, we proposed a new evolutionary classification model in this paper. The core of the prediction model is a kern...
This article presents a new method based on meta-heuristic algorithm for maximum power point tracking (MPPT) in photovoltaic systems. In this new method, the SALP Swarm Algorithm (SSA) is used instead of classic methods such as the Perturb and Observ...
A novel methodology based on the recent metaheuristic optimization algorithm Salp Swarm Algorithm (SSA) for locating and optimal sizing of renewable distributed generators (RDGs) and shunt capacitor banks (SCBs) on radial distribution networks (RDNs)...
This paper presents a novel approach to water access segmentation by introducing an improved version of the Salp Swarm Algorithm (ISSA), addressing the complex challenge of household water access classification in developing regions. The proposed enh...
In order to address the diverse and personalized needs of consumers for fresh products, as well as to enhance the efficiency and safety of fresh product delivery, this paper proposes an integer programming model aimed at minimizing total distribution...
Airborne Wind Energy (AWE) systems offer benefits such as high altitude access to stronger and more stable winds, reduced environmental impact, and cost effective infrastructure. However, these systems face several challenges including complex flight...
Modeling errors and external disturbances have significant impacts on the control accuracy of robotic arm trajectory tracking. To address this issue, this paper proposes a novel method, the neural network terminal sliding mode control (ALSSA-RBFTSM),...
This paper concerns the problem of vibration reduction during milling. For this purpose, it is proposed that the standard supports of the workpiece be replaced with adjustable stiffness supports. This affects the modal parameters of the whole system,...
The islanded mode of the microgrid (MG) operation faces more power quality challenges as compared to grid-tied mode. Unlike the grid-tied MG operation, where the voltage magnitude and frequency of the power system are regulated by the utility grid, i...
(1) Background: Feature selection is the biggest challenge in feature-rich sentiment analysis to select the best (relevant) feature set, offer information about the relationships between features (informative), and be noise-free from high-dimensional...
In this paper, we propose a modified hybrid Salp Swarm Algorithm (SSA) and Aquila Optimizer (AO) named IHSSAO for UAV path planning in complex terrain. The primary logic of the proposed IHSSAO is to enhance the performance of AO by introducing the le...
The optimal reactive power dispatch (ORPD) problem represents a fundamental concern in the efficient and reliable operation of power systems, based on the proper coordination of numerous devices. Therefore, the ORPD calculation is an elaborate nonlin...
Motor fault diagnosis is an important task in the operational monitoring of electrical machines in manufacturing. This study proposes an effective bearing fault diagnosis model for electrical machinery based on machine learning techniques. The propos...
To improve the control ability of proportional–integral–derivative (PID) controllers and increase the stability of force actuator systems, this paper introduces a PID controller based on the self-growing lévy-flight salp swarm algo...
Given the importance of renewable energy sources in distribution systems, this article addresses the problem of locating and determining the capacity of these sources, namely, wind turbines and solar panels. To solve this optimization problem, a new...
The economic model derived from the supply and demand of crude oil prices is a significant component that measures economic development and sustainability. Therefore, it is essential to mitigate crude oil price volatility risks by establishing models...
With the development of computationally intensive applications, the demand for edge cloud computing systems has increased, creating significant challenges for edge cloud computing networks. In this paper, we consider a simple three-tier computational...
In recent years, a pronounced transition to the exploitation of renewable energy sources has be observed worldwide, driven by current climate concerns and the scarcity of conventional fuels. However, this paradigm shift is accompanied by new challeng...
To address the multi-objective flexible job shop scheduling problem in rolling production mode (FJSP-RPM), this study proposes a Multi Objective Improved of Salp Swarm Algorithm (MISSA) that simultaneously optimizes equipment utilization and total ta...
Voltage source converter (VSC) has been extensively applied in renewable energy systems which can rapidly regulate the active and reactive power. This paper aims at developing a novel optimal nonlinear adaptive control (ONAC) scheme to control VSC in...
In this study, an optimization method for the motion trajectory of attitude actuators was investigated in order to improve assembly efficiency in the automatic docking process of large components. The self-developed dual-attitude adjustment mechanism...
This paper presents a new methodology to simultaneously solve the optimal conductor selection and optimal phase-balancing problems in unbalanced three-phase distribution systems. Both problems were represented by means of a mathematical model known a...
To enhance the sustainable power regulation capability of hydroelectric unit regulation systems (HURS) under modern power system requirements, this paper proposes an optimal linear quadratic regulator (LQR)-based power control strategy optimized usin...
Owing to the superior transient and steady-state performance of the fractional-order proportional-integral-derivative (FOPID) controller over its conventional counterpart, this paper exploited its application in an automatic voltage regulator (AVR) s...
Multi-robot exploration means constructing a finite map using a group of robots in an obstacle chaotic space. Uncertainties are reduced by distributing search tasks to robots and computing the best action in real time. Many previous methods are based...
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