sine cosine algorithm
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Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 617
Author(s):  
P. Arun Mozhi Devan ◽  
Fawnizu Azmadi Hussin ◽  
Rosdiazli B. Ibrahim ◽  
Kishore Bingi ◽  
M. Nagarajapandian ◽  
...  

This paper proposes a novel hybrid arithmetic–trigonometric optimization algorithm (ATOA) using different trigonometric functions for complex and continuously evolving real-time problems. The proposed algorithm adopts different trigonometric functions, namely sin, cos, and tan, with the conventional sine cosine algorithm (SCA) and arithmetic optimization algorithm (AOA) to improve the convergence rate and optimal search area in the exploration and exploitation phases. The proposed algorithm is simulated with 33 distinct optimization test problems consisting of multiple dimensions to showcase the effectiveness of ATOA. Furthermore, the different variants of the ATOA optimization technique are used to obtain the controller parameters for the real-time pressure process plant to investigate its performance. The obtained results have shown a remarkable performance improvement compared with the existing algorithms.


2022 ◽  
Vol 9 ◽  
Author(s):  
Mohammad Ehteram ◽  
Fatemeh Panahi ◽  
Ali Najah Ahmed ◽  
Amir H. Mosavi ◽  
Ahmed El-Shafie

Predicting evaporation is essential for managing water resources in basins. Improvement of the prediction accuracy is essential to identify adequate inputs on evaporation. In this study, artificial neural network (ANN) is coupled with several evolutionary algorithms, i.e., capuchin search algorithm (CSA), firefly algorithm (FFA), sine cosine algorithm (SCA), and genetic algorithm (GA) for robust training to predict daily evaporation of seven synoptic stations with different climates. The inclusive multiple model (IMM) is then used to predict evaporation based on established hybrid ANN models. The adjusting model parameters of the current study is a major challenge. Also, another challenge is the selection of the best inputs to the models. The IMM model had significantly improved the root mean square error (RMSE) and Nash Sutcliffe efficiency (NSE) values of all the proposed models. The results for all stations indicated that the IMM model and ANN-CSA could outperform other models. The RMSE of the IMM was 18, 21, 22, 30, and 43% lower than those of the ANN-CSA, ANN-SCA, ANN-FFA, ANN-GA, and ANN models in the Sharekord station. The MAE of the IMM was 0.112 mm/day, while it was 0.189 mm/day, 0.267 mm/day, 0.267 mm/day, 0.389 mm/day, 0.456 mm/day, and 0.512 mm/day for the ANN-CSA, ANN-SCA, and ANN-FFA, ANN-GA, and ANN models, respectively, in the Tehran station. The current study proved that the inclusive multiple models based on improved ANN models considering the fuzzy reasoning had the high ability to predict evaporation.


2022 ◽  
Vol 14 (1) ◽  
pp. 541
Author(s):  
Mahdiyeh Eslami ◽  
Mehdi Neshat ◽  
Saifulnizam Abd. Khalid

This paper presents an effective hybrid optimization technique based on a chaotic sine cosine algorithm (CSCA) and pattern search (PS) for the coordinated design of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. For this purpose, the design problem is considered as an optimization problem whose decision variables are the controllers’ parameters. Due to the nonlinearities of large, interconnected power systems, methods capable of handling any nonlinearity of power networks are preferable. In this regard, a nonlinear time domain-based objective function was used. Then, the proposed hybrid chaotic sine cosine pattern search (hCSC-PS) algorithm was employed for solving this optimization problem. The proposed method employed the global search ability of SCA and the local search ability of PS. The performance of the new hCSC-PS was investigated using a set of benchmark functions, and then the results were compared with those of the standard SCA and some other methods from the literature. In addition, a case study from the literature is considered to evaluate the efficiency of the proposed hCSC-PS for the coordinated design of controllers in the power system. PSSs and additional SVC controllers are being considered to demonstrate the feasibility of the new technique. In order to ensure the robustness and performance of the proposed controller, the objective function is evaluated for various extreme loading conditions and system configurations. The numerical investigations show that the new approach may provide better optimal damping and outperforms previous methods. Nonlinear time-domain simulation shows the superiority of the proposed controller and its ability in providing efficient damping of electromechanical oscillations.


2022 ◽  
Vol 71 (2) ◽  
pp. 3533-3556
Author(s):  
Siti Julia Rosli ◽  
Hasliza A Rahim ◽  
Khairul Najmy Abdul Rani ◽  
Ruzelita Ngadiran ◽  
Wan Azani Mustafa ◽  
...  

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 118
Author(s):  
Jiali Zi ◽  
Danju Lv ◽  
Jiang Liu ◽  
Xin Huang ◽  
Wang Yao ◽  
...  

In recent years, separating effective target signals from mixed signals has become a hot and challenging topic in signal research. The SI-BSS (Blind source separation (BSS) based on swarm intelligence (SI) algorithm) has become an effective method for the linear mixture BSS. However, the SI-BSS has the problem of incomplete separation, as not all the signal sources can be separated. An improved algorithm for BSS with SI based on signal cross-correlation (SI-XBSS) is proposed in this paper. Our method created a candidate separation pool that contains more separated signals than the traditional SI-BSS does; it identified the final separated signals by the value of the minimum cross-correlation in the pool. Compared with the traditional SI-BSS, the SI-XBSS was applied in six SI algorithms (Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), Sine Cosine Algorithm (SCA), Butterfly Optimization Algorithm (BOA), and Crow Search Algorithm (CSA)). The results showed that the SI-XBSS could effectively achieve a higher separation success rate, which was over 35% higher than traditional SI-BSS on average. Moreover, SI-SDR increased by 14.72 on average.


2021 ◽  
pp. 116417
Author(s):  
Qusay Shihab Hamad ◽  
Hussein Samma ◽  
Shahrel Azmin Suandi ◽  
Junita Mohamad-Saleh

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