Tuning PID Controllers Based on Hybrid Arithmetic Optimization Algorithm and Artificial Gorilla Troop Optimization for Micro-Robotics Systems

IEEE Access, Год журнала: 2023, Номер 11, С. 27138 - 27154

Опубликована: Янв. 1, 2023

Micro particles have the potentials to be used for many medical purposes in-side human body such as drug delivery and other operations. This paper attempts provide a thorough comparison between five meta-heuristic search algorithms: Arithmetic optimization algorithm (AOA), Artificial Gorilla troop's (GTO), Seagull (SOA), Parasitism-predation Algorithm (PPA), hybrid AOA GTO (HAOAGTO). These approaches were calculate PID controller optimal indicators with application of different functions, including Integral Absolute Error (IAE), Time Multiplied by Square (ITSE), multiplied square (ISTES), (ISE), ( (ISTSE), (ITAE). Every method controlling was presented in MATLAB Simulink numerical model. It is observed that PPA technique achieves highest values best fitness value simulation results among control approaches, while HAOAGTO approach reduces function compared techniques used. The indicate all ISTES choice optimizing parameters.

Язык: Английский

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Addressing feature selection and extreme learning machine tuning by diversity-oriented social network search: an application for phishing websites detection

Complex & Intelligent Systems, Год журнала: 2023, Номер 9(6), С. 7269 - 7304

Опубликована: Июнь 28, 2023

Abstract Feature selection and hyper-parameters optimization (tuning) are two of the most important challenging tasks in machine learning. To achieve satisfying performance, every learning model has to be adjusted for a specific problem, as efficient universal approach does not exist. In addition, data sets contain irrelevant redundant features that can even have negative influence on model’s performance. Machine applied almost everywhere; however, due high risks involved with growing number malicious, phishing websites world wide web, feature tuning this research addressed particular problem. Notwithstanding many metaheuristics been devised both challenges, there is still much space improvements. Therefore, exhibited manuscript tries improve website detection by extreme utilizes relevant subset features. accomplish goal, novel diversity-oriented social network search algorithm developed incorporated into two-level cooperative framework. The proposed compared six other cutting-edge algorithms, were also implemented framework tested under same experimental conditions. All employed level 1 perform task. best-obtained then used input 2, where all algorithms machine. Tuning referring neurons hidden layers weights biases initialization. For evaluation purposes, three different sizes classes, retrieved from UCI Kaggle repositories, methods terms classification error, separately 2 over several independent runs, detailed metrics final outcomes (output layer 2), including precision, recall, f1 score, receiver operating characteristics precision–recall area curves. Furthermore, an additional experiment conducted, only used, establish performance features, which represents large-scale NP-hard global challenge. Finally, according results statistical tests, findings suggest average obtains better achievements than competitors challenges sets. SHapley Additive exPlanations analysis best-performing was determine influential

Язык: Английский

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An efficient k-NN-based rao optimization method for optimal discrete sizing of truss structures

Applied Soft Computing, Год журнала: 2024, Номер 154, С. 111373 - 111373

Опубликована: Фев. 9, 2024

Язык: Английский

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Image Registration Using the Arithmetic Optimization Algorithm for Robotic Visual Servoing

International Journal of Computational Intelligence Systems, Год журнала: 2025, Номер 18(1)

Опубликована: Янв. 8, 2025

Visual servoing using image registration is a method employed in robotics to control the movement of system visual information. In this context, we propose new intensity-based algorithm (IBIR) that uses information derived from images acquired at different times or views determine parameters geometric transformations needed align these images. The Arithmetic Optimization Algorithm (AOA) used optimize parameters, minimizing difference between be aligned. proposed algorithm, Intensity-Based Image Registration via Optimisation (IBIRAOA), robust data fluctuations and perturbations can avoid local optima. Simulation results prove importance efficiency terms computation time similarity aligned compared other methods based on various metaheuristics. addition, our confirm significant improvement trajectory wheeled mobile robot, thus reinforcing overall effectiveness practical navigation robotic applications.

Язык: Английский

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Seismic performance-based design optimization of 2D steel chevron-braced frames using ACO algorithm and nonlinear pushover analysis

Structural and Multidisciplinary Optimization, Год журнала: 2025, Номер 68(1)

Опубликована: Янв. 1, 2025

Язык: Английский

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Optimization of time–cost–quality-CO2 emission trade-off problems via super oppositional TLBO algorithm

Asian Journal of Civil Engineering, Год журнала: 2025, Номер unknown

Опубликована: Март 18, 2025

Язык: Английский

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An efficient DBSCAN optimized by arithmetic optimization algorithm with opposition-based learning

The Journal of Supercomputing, Год журнала: 2022, Номер 78(18), С. 19566 - 19604

Опубликована: Июнь 26, 2022

Abstract As unsupervised learning algorithm, clustering algorithm is widely used in data processing field. Density-based spatial of applications with noise (DBSCAN), as a common can achieve clusters via finding high-density areas separated by low-density based on cluster density. Different from other methods, DBSCAN work well for any shape the database and effectively exceptional data. However, employment DBSCAN, parameters, EPS MinPts, need to be preset different object, which greatly influences performance DBSCAN. To automatic optimization parameters improve we proposed an improved optimized arithmetic (AOA) opposition-based (OBL) named OBLAOA-DBSCAN. In details, reverse search capability OBL added AOA obtaining proper adaptive parameter optimization. addition, our OBLAOA optimizer compared standard several latest meta heuristic algorithms 8 benchmark functions CEC2021, validates exploration improvement OBL. validate OBLAOA-DBSCAN, 5 classical methods 10 real datasets are chosen compare models according computational cost accuracy. Based experimental results, obtain two conclusions: (1) OBLAOA-DBSCAN provide highly accurately more efficiently; (2) significantly ability, better optimal parameters.

Язык: Английский

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LMRAOA: An improved arithmetic optimization algorithm with multi-leader and high-speed jumping based on opposition-based learning solving engineering and numerical problems

Alexandria Engineering Journal, Год журнала: 2022, Номер 61(12), С. 12367 - 12403

Опубликована: Июнь 20, 2022

Язык: Английский

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An improved bat algorithms for optimization design of truss structures

Structures, Год журнала: 2022, Номер 47, С. 2240 - 2258

Опубликована: Дек. 22, 2022

Язык: Английский

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A Novel Meta-Heuristic Algorithm for Numerical and Engineering Optimization Problems: Piranha Foraging Optimization Algorithm (PFOA)

IEEE Access, Год журнала: 2023, Номер 11, С. 92505 - 92522

Опубликована: Янв. 1, 2023

This paper provides a novel meta-heuristic optimization algorithm for solving continuous problems efficiently in the field of numerical and engineering optimization: Piranha Foraging Optimization Algorithm (PFOA). The is inspired by flexible mobile foraging behaviour piranha swarm divides their behavior into three patterns: localized group attack, bloodthirsty cluster attack scavenging foraging, simulates above behaviors to construct two dynamic search processes exploration exploitation. PFOA uses strategies non-linear parameter control, population survival reverse evasion enable populations have better diversity at different stages help find solutions. To gain insight performance PFOA, visualization methods were used assess efficiency analyse impact characteristics modes, sensitivity parameters size on algorithm. was further tested with 27 CEC benchmark functions four real design problems, results compared 13 well-known meta-heuristics. Test based statistical such as box-line plots, Wilcoxon rank sum test Friedman multiple dimensions (30, 50, 100 fixed dimensions) show significant differences other algorithms that stable improvement. unique advantages terms equilibrium convergence speed can avoid getting trapped local optimum regions effectively solve complex spaces.

Язык: Английский

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