Article
Computer Science, Information Systems
Prasanjit Chakraborty, Sukanta Nama, Apu Kumar Saha
Summary: In this paper, a hybrid slime mould algorithm is proposed to address the issue of local optima stagnation and improve the exploitation ability of the algorithm. The effectiveness of the proposed algorithm is demonstrated through comparisons with other metaheuristic algorithms on benchmark problems and engineering optimization problems.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
Wali Khan Mashwani, Ihsan Mehmood, Maharani Abu Bakar, Ismail Koccak
Summary: The paper introduces the Bat algorithm (BA) and the modified Bat algorithm (MBA) in swarm intelligence, where BA utilizes echolocation behavior of bats for search and MBA aims to enhance search capabilities. The study evaluates the performance of MBA using benchmark functions from the 2005 IEEE Congress on Evolutionary Computation, analyzing the impact of different temperature values on the algorithm.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Apu Kumar Saha
Summary: This paper presents a modified sine cosine algorithm (MAMSCA) that addresses the shortcomings of the original algorithm by balancing global and local search and introducing additional variation to the population. The proposed algorithm demonstrates significant improvement in solving real-world challenges.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Jiao Hu, Wenyong Gui, Ali Asghar Heidari, Zhennao Cai, Guoxi Liang, Huiling Chen, Zhifang Pan
Summary: The dispersed foraging slime mould algorithm (DFSMA) is proposed as an enhanced version of the slime mould algorithm (SMA) to address the limitations of SMA in solving multimodal and hybrid functions. Experimental results demonstrate that DFSMA outperforms other algorithms in terms of convergence speed and accuracy. Furthermore, the binary DFSMA (BDFSMA) is evaluated and found to have improved performance in classification accuracy and feature selection compared to other optimization algorithms.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Information Systems
Liang Zeng, Junyang Shi, Ming Li, Shanshan Wang
Summary: The Squirrel Search Algorithm (SSA) is an optimization method that enhances its performance by taking inspiration from the foraging and gliding behavior of squirrels. This paper proposes an improved squirrel search algorithm embedded with the Sine Cosine Algorithm (SCSSA) to address issues such as falling into local optima and premature convergence. Extensive experiments show that SCSSA consistently outperforms other comparison algorithms in terms of numerical optimization and convergence rate.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Energy & Fuels
Yuanye Wei, Yongquan Zhou, Qifang Luo, Wu Deng
Summary: The paper introduces an improved slime mould algorithm (ISMA) to solve the optimal reactive power dispatch (ORPD) problem, and the performance evaluation and experimental results show that ISMA outperforms in accuracy and computational efficiency.
Article
Computer Science, Information Systems
Sushmita Sharma, Apu Kumar Saha, Susmita Roy, Seyedali Mirjalili, Sukanta Nama
Summary: This paper proposes a hybrid sine cosine butterfly optimization algorithm (m-SCBOA) that combines the modified butterfly optimization algorithm with the sine cosine algorithm to enhance search capabilities. Experimental results and comparisons demonstrate the superiority of the proposed algorithm. Furthermore, the algorithm is also validated through solving real-world engineering design problems and parameter optimization problems.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Article
Automation & Control Systems
M. H. Suid, M. A. Ahmad
Summary: This paper proposes a sigmoid-based PID (SPID) controller for the Automatic Voltage Regulator (AVR) system to improve the dynamic response and control accuracy. The parameters of the SPID controller are obtained using a heuristic optimization method called Nonlinear Sine Cosine Algorithm (NSCA). The proposed SPID controller is validated and shown to be highly effective and greatly improve the transient response of the AVR system compared to modern heuristic optimization based PID controllers.
Article
Computer Science, Artificial Intelligence
Ahmed A. Ewees, Fatma H. Ismail, Ahmed T. Sahlol
Summary: This paper proposes a hybrid approach for solving global optimization and feature selection problems, combining Gradient-Based Optimizer and Slime Mould Algorithm. The experimental results demonstrate that this approach outperforms other algorithms in terms of performance, speed, and stability.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Automation & Control Systems
Changlun Li, Ke Liang, Yuan Chen, Mingzhang Pan
Summary: This study proposes an exploitation-boosted sine cosine algorithm (EBSCA) to improve the performance of the original SCA. By designing a new position-updated equation and dynamically adjusting the information weights, the EBSCA algorithm enhances the exploitation ability while avoiding over-exploitation. Furthermore, the integration of quantization orthogonal crossover strategy with SCA improves the efficiency of the searching space. Experimental results demonstrate that EBSCA outperforms SCA and shows higher competitiveness compared to other algorithms.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Reza Moghdani, Mohamed Abd Elaziz, Davood Mohammadi, Nabil Neggaz
Summary: This study presents a modified VPLSCA algorithm using sine cosine algorithm operators to obtain more accurate solutions in volleyball simulations, which showed promising results compared to other metaheuristic algorithms. The algorithm utilizes volleyball metaphors to find better solutions and has been tested on various functions and optimization problems with reasonable outcomes.
ENGINEERING WITH COMPUTERS
(2021)
Article
Thermodynamics
Yun Liu, Ali Asghar Heidari, Xiaojia Ye, Guoxi Liang, Huiling Chen, Caitou He
Summary: The study presents an advanced SMA-based algorithm, CNMSMA, incorporating Nelder-Mead simplex strategy and chaotic map, for efficiently and accurately estimating the unknown parameters of photovoltaic solar cells, demonstrating excellent convergence rapidity and stability.
Article
Engineering, Multidisciplinary
Md. Shadman Abid, Hasan Jamil Apon, Ashik Ahmed, Khandaker Adil Morshed
Summary: This paper presents an optimal load shedding technique using the Chaotic Slime Mould Algorithm (CSMA) to achieve efficient islanding operation in a distribution system with Distributed Generation (DG). The proposed method outperforms other algorithms in terms of remaining load and voltage stability.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Article
Computer Science, Interdisciplinary Applications
Yundi Rao, Dengxu He, Liangdong Qu
Summary: The Crow Search Algorithm is a new meta-heuristic optimizer inspired by the intelligent behavior of crows, and it has great potential for applications in engineering. This paper introduces a hybrid algorithm called PSCCSA, which combines the Crow Search Algorithm with a probability simplified sine cosine algorithm to overcome the limitations of blind location updates in CSA. The results of comparing the proposed algorithm with five other meta-heuristic algorithms and applying it to four classic engineering problems demonstrate its feasibility and effectiveness.
ENGINEERING WITH COMPUTERS
(2023)
Article
Computer Science, Interdisciplinary Applications
Xi Liang, Zhennao Cai, Mingjing Wang, Xuehua Zhao, Huiling Chen, Chengye Li
Summary: This study proposes an improved sine-cosine algorithm (SCA) for global optimization tasks, called chaotic oppositional SCA (COSCA), which strengthens the exploration and exploitation capability of the basic SCA by utilizing chaotic local search strategy and opposition-based learning strategy. Simulation experiments show that COSCA significantly improves the global optimization ability and outperforms other algorithms, and it also effectively solves complex engineering problems with constraints.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Artificial Intelligence
Salih Berkan Aydemir, Sevcan Yilmaz Gunduz
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Salih Berkan Aydemir, Sevcan Yilmaz Gunduz
Summary: This paper introduces neutrality average and neutrality geometric aggregation operators based on power aggregation (PA), and proposes a general score function for q-rung orthopair fuzzy sets (q-ROFSs). The PA operators reduce the impact of excessively high or low arguments and emphasize interrelationships between attributes. The proposed neutrality aggregation operator provides reliable results by considering neutrality among decision-makers, and q-ROFSs offer a wider evaluation for decision-makers.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Funda Kutlu Onay, Salih Berkan Aydemir
Summary: Chaotic maps are utilized in the Hunger Games Search (HGS) algorithm to control random values for faster and more stable convergence. The chaotic HGS algorithm shows promising results when applied to real engineering problems and outperforms classical HGS and state-of-the-art algorithms in the literature. Study published by Elsevier B.V. and copyright by the International Association for Mathematics and Computers in Simulation (IMACS).
MATHEMATICS AND COMPUTERS IN SIMULATION
(2022)
Article
Mathematics, Applied
Tahir Aliyev Azeroglu, Bulent Nafi Ornek, Timur Duzenli
Summary: An inequality for a transfer function at poles located on the imaginary axis in the right half plane is obtained in this paper, along with the extremal function. Root-locus curves are plotted to interpret the results in terms of control theory. The extremal function obtained from the proposed theorem can be used to determine marginally and asymptotically stable transfer functions.
EVOLUTION EQUATIONS AND CONTROL THEORY
(2022)
Article
Computer Science, Software Engineering
Berkant Konakoglu, Salih Berkan Aydemir, Funda Kutlu Onay
Summary: This article examines the efficiency of a new hybrid learning method, ANN-GBO, in determining local geoid. The results show that ANN-GBO outperforms other methods in terms of prediction accuracy.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Tansu Temel, Salih Berkan Aydemir, Yasar Hoscan
Summary: This study proposes the use of the power Muirhead mean operator in the spherical normal fuzzy sets environment to solve multiple attribute decision-making problems. The proposed operators produce effective results in terms of their suitability to real-world problems and the relationship between their criteria.
COMPLEX & INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Salih Berkan Aydemir
Summary: A new optimization method combining chaotic maps and arithmetic optimization algorithm (CAOA) is proposed in this study. The experimental results show that the proposed hybrid algorithm achieves more successful and promising results in solving optimization problems compared to the original arithmetic optimization algorithm.
EVOLUTIONARY INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Bulent Nafi Ornek, Salih Berkan Aydemir, Timur Duzenli, Bilal Ozak
Summary: This study proposes a complex valued activation function for classification problems with complex valued data, and analyzes its performance using a complex-valued extreme learning classifier. The proposed activation function is obtained by performing extremal analyses of the inequalities derived from the boundary Schwarz lemma. Simulation results show that the proposed activation function outperforms other activation functions in terms of classification accuracy and function approximation.
Article
Optics
Timur Duzenli, Funda Kutlu Onay, Salih Berkan Aydemir
Summary: This study aims to enhance the convergence performance in photovoltaic systems by using two improved versions of the honey badger algorithm. The proposed algorithms are evaluated on different datasets and photovoltaic models, and show high performance in parameter estimation and optimization.
Article
Computer Science, Software Engineering
Salih Berkan Aydemir, Funda Kutlu Onay
Summary: The Marine Predator Algorithm (MPA) is a powerful optimization algorithm that effectively converges on complex benchmark functions. However, it can fall into a local optimum and lacks comprehensive search during the exploration phase. Therefore, this study improves MPA by integrating elite evolution and elite random mutation strategies, resulting in the Elite Evolution Strategy MPA (EEMPA). EEMPA achieves comprehensive scanning of the solution space and reduces the risk of falling into local optima.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Salih Berkan Aydemir
Summary: This article introduces two different strategies in the Marine Predator Algorithm, Taylor-based optimal neighborhood strategy (TNS) and asymmetric search space with dynamic option-based learning, to address the algorithm's issues with local optima, search capability, and stagnation. Experimental results show that the improved algorithm with these strategies has strong competitiveness in terms of convergence accuracy and achieving the global optimum, making it promising for practical applications.
ADVANCES IN ENGINEERING SOFTWARE
(2023)
Article
Mathematics, Applied
Bulent Nafi Ornek, Timur Duzenli
Article
Computer Science, Interdisciplinary Applications
Vitaly Chernik, Pavel Buklemishev
Summary: The paper introduces a simple 2D model for describing the cell motility on a homogeneous isotropic surface. The model incorporates the dynamics of complex actomyosin liquid, which affects the boundary dynamics and cell motility. It consists of a system of equations with a free boundary domain and includes a non-local term. The numerical solution of this model is presented in this work.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Hasan Karjoun, Abdelaziz Beljadid
Summary: In this study, we developed a numerical model based on the depth-averaged shallow water equations to simulate flows through vegetation field. The model takes into account the drag and inertia forces induced by vegetation, using different formulations for the stem drag coefficient. Turbulence induced by vegetation is also considered through the addition of diffusion terms in the momentum equations. The proposed numerical model is validated through numerical simulations and shows good accuracy in simulating overland flows under vegetation effects.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Bechir Naffeti, Hamadi Ammar, Walid Ben Aribi
Summary: This paper proposes a branch and bound multidimensional Holder optimization method, which converts a multivariate objective function into a single variable function and minimizes it using an iterative optimization method. The method is applied to solve a parameters identification problem resulting from the increase in infections, providing information about the prevalence and infection force.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Heba F. Eid, Erik Cuevas, Romany F. Mansour
Summary: The proposed modified Bonobo optimizer algorithm dynamically adjusts the trajectory of each search agent to overcome the flaw of the original algorithm and improve the performance and solution quality by exploring and exploiting different regions of the solution space.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Farshid Mehrdoust, Idin Noorani, Juho Kanniainen
Summary: This paper proposes a Markov-switching model to evaluate the dynamics of commodity futures and spot prices, and introduces a hidden Markov chain to model the sudden jumps in commodity prices. The model is calibrated using the crude oil spot price and estimation-maximization algorithm. The study also evaluates European call options written on crude oil futures under the regime-switching model and derives Greek formulas for risk assessment. The importance of this paper is rated at 8 out of 10.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Rupa Mishra, Tapas Kumar Saha
Summary: This paper presents a control scheme for distributed generation units to operate in stand-alone and grid-connected modes, with a smooth transition between the two. The control strategy includes predictive control for voltage and frequency regulation in stand-alone mode, and power control for symmetrical and unbalanced grid voltage conditions in grid-connected mode. The proposed control method improves power factor, reduces grid current harmonics, and eliminates grid frequency ripple.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Yu Wang, Yang Tian, Yida Guo, Haoping Wang
Summary: This paper proposes a multi-level control strategy for lower limb patient-exoskeleton coupling system (LLPECS) in rehabilitation training based on active torque. The controller consists of three sub-controllers: gait adjustment layer, interaction torque design layer, and trajectory tracking layer. The effectiveness of the proposed control strategy is demonstrated through co-simulations in the SimMechanics environment using an exoskeleton virtual prototype developed in SolidWorks.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Takuji Arai, Yuto Imai
Summary: The Barndorff-Nielsen and Shephard model is a jump-type stochastic volatility model, and this paper proposes two simulation methods for computing option prices under a representative martingale measure. The performance of these methods is evaluated through numerical experiments.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Wanai Li
Summary: This paper proposes a new framework that combines quadrature-based and quadrature-free discontinuous Galerkin methods and applies them to triangular and tetrahedral grids. Four different DG schemes are derived by choosing specific test functions and collocation points, improving computational efficiency and ease of code implementation.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Xiyuan Chen, Qiubao Wang
Summary: This paper introduces a technique that combines dynamical mechanisms and machine learning to reduce dimensionality in high-dimensional complex systems. The method utilizes Hopf bifurcation theory to establish a model paradigm and utilizes machine learning to train location parameters. The effectiveness and robustness of the proposed method are tested and validated through experiments and simulations.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Muhammad Farman, Aqeel Ahmad, Anum Zehra, Kottakkaran Sooppy Nisar, Evren Hincal, Ali Akgul
Summary: Diabetes is a significant public health issue that affects millions of people worldwide. This study proposes a mathematical model to understand the mechanisms of glucose homeostasis, providing valuable insights for diabetes management. The model incorporates fractional operators and analyzes the impact of a new wave of dynamical transmission on equilibrium points, offering a comprehensive understanding of glucose homeostasis.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Gholamreza Shobeyri
Summary: This study introduces two improved Laplacian models for more accurate simulation of free surface flows in the context of the MPS method. The higher accuracy of these models compared to the traditional methods is verified through solving 2D Poisson equations and solving three benchmark free surface flow problems. These models can also resolve the issue of wave damping in the original MPS computations.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Qiang Li, Jinling Liang, Weiqiang Gong, Kai Wang, Jinling Wang
Summary: This paper addresses the problem of nonfragile state estimation for semi-Markovian switching complex-valued networks with time-varying delay. By constructing an event-triggered generator and solving matrix inequalities, less conservative criteria are obtained, and the gains of the nonfragile estimator are explicitly designed. A numerical example is provided to demonstrate the effectiveness of the proposed estimation scheme.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Gengen Zhang, Jingyu Li, Qiong-Ao Huang
Summary: In this paper, a novel class of unconditionally energy stable schemes are constructed for solving gradient flow models by combining the relaxed scalar auxiliary variable (SAV) approach with the linear multistep technique. The proposed schemes achieve second-order temporal accuracy and strictly unconditional energy stability.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
S. Clain, J. Figueiredo
Summary: This study proposes a detailed construction of a very high-order polynomial representation and introduces a functional to assess the quality of the reconstruction. Several optimization techniques are implemented and their advantages in terms of accuracy and stability are demonstrated.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)