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water cycle algorithm with adaptive sea and rivers and enhanced position updating strategy for numerical optimization

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NEURAL COMPUTING & APPLICATIONS 2023年第18期35卷 13387-13416页

作者： Tian, Mengnan Gao, Xingbao Yan, Xueqing Xian Polytech Univ Sch Sci Jinhua South Rd Xian 710048 Shaanxi Peoples R China Shaanxi Normal Univ Sch Math & Stat West Changan Ave Xian 710062 Shaanxi Peoples R China Shaanxi Normal Univ Sch Comp Sci West Changan Ave Xian 710062 Shaanxi Peoples R China

In this paper, a novel water cycle algorithm is presented by dynamically assigning sea and rivers and devising an enhanced position updating strategy. To effectively maintain the diversity of solutions and ensure the convergence of algorithm, an adaptive distance-based assignment mechanism is first developed to set sea, rivers and their corresponding streams. In this mechanism, the fitness values and position information of solutions are simultaneously considered, and the total number of sea and rivers is nonlinearly reduced during the search process. Meanwhile, an enhanced position updating strategy is designed to update the solutions by incorporating both the gravitational search and greedy strategy. Moreover, a modified evaporation operation is further proposed to dynamically refresh the search capability of algorithm by properly making full use of the promising information of solutions. Differing from the existing WCA variants, the proposed algorithm dynamically assigns sea, rivers and their streams, additionally incorporates the gravitational search and greedy strategy, and fully exploits the obtained promising information in the raining process. Then it could availably strengthen the search effectiveness and balance the exploration and exploitation. Finally, the performance of the proposed algorithm is evaluated by comparing with 12 typical algorithms on 30 CEC2017 benchmark functions. Numerical results show that the proposed algorithm has better performance.

关键词： Global optimization water cycle algorithm Sea and rivers assignment Position updating strategy

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water cycle algorithm: an approach for improvement of navigational strategy of multiple humanoid robots

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ROBOTICA 2022年第3期40卷 798-816页

作者： Muni, Manoj Kumar Kumar, Saroj Parhi, Dayal R. Pandey, Krishna Kant Indira Gandhi Inst Technol Dept Mech Engn Sarang 759146 Odisha India Natl Inst Technol Robot Lab Dept Mech Engn Rourkela 769008 Odisha India GH Raisoni Inst Engn & Technol Dept Mech Engn Pune 412207 Maharashtra India

This paper presents an efficient water cycle algorithm based on the processes of water cycle with movement of streams and rivers in to the sea. This optimization algorithm is applied to obtain the optimal feasible path with minimum travel duration during motion planning of both single and multiple humanoid robots in both static and dynamic cluttered environments. This technique discards the rainfall process considering falling water droplets forming streams during raining and the process of flowing. The flowing process searches the solution space and finds the more accurate solution and represents the local search. Motion planning of humanoids is carried out in V-REP software. The performance of proposed algorithm is tested in experimental scenario under laboratory conditions and shows the developed algorithm performs well in terms of obtaining optimal path length and minimum time span of travel. Here, navigational analysis has been performed on both single as well as multiple humanoid robots. Statistical analysis of results obtained from both simulation and experimental environments is carried out for both single and multiple humanoids, along with the comparison with another existing optimization technique that indicate the strength and effectiveness of the proposed water cycle algorithm.

关键词： water cycle algorithm humanoid NAO V-REP simulation experiment statistical analysis

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Optimization of dynamic control systems using water cycle algorithm

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2024年第8期361卷

作者： Alimorad, Hajar Jahrom Univ Dept Math POB 74135-111 Jahrom Iran

In this paper, path optimization in dynamic control systems was performed using water cycle algorithm. The core principles and assumptions that guide the suggested technique are drawn from nature and are based on observations of the water cycle process and how rivers and streams naturally flow into the sea. The water cycle algorithm has been recognized as a reliable method for dealing with large-scale optimization challenges, largely because of its proficient exploitation and exploration capabilities. This algorithm does not require the continuity of functions when specifying the issue, unlike many gradient -based approaches. This is achieved through the use of a simple mathematical model that represents the water cycle process. This model is used to simulate the movement of water droplets in a cloud, where each water droplet represents a potential solution to the optimization problem. Although water cycle optimization has been utilized successfully to tackle optimization issues, this is the first time dynamic control optimization has been used. The control problem is switched out for an optimum programming problem in order to find optimal pathways utilizing the Shifted Chebyshev polynomial. The water cycle method was then used to resolve the new issue. The numerical results demonstrate the excellent precision with which this search method can discover solutions.

关键词： Dynamic Constraint problems Control systems Shifted Chebyshev polynomial water cycle algorithm

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Opposition and Chaos-Based water cycle algorithm on Engineering Benchmark Problems

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INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS 2025年第5期35卷

作者： Datta, Monalisa Sarkar, Dipu Das, Soumyabrata Natl Inst Technol Nagaland Elect & Elect Engn Dept Dimapur 797103 Nagaland India Techno Int New Town Elect Engn Dept Chakpachuria India Visveswaraya Natl Inst Technol Elect Engn Nagpur India

Chaos-based learning is a popular method that combines with optimized techniques to achieve the best fitness values by preventing early convergence and improving initial conditions. Chaos enhances the search process, while opposition learning helps improve the population development matrix, ultimately boosting result quality. This paper introduces two new concepts in machine learning. It proposes an improved Opposition and Chaos-based water cycle algorithm (OCWCA) to effectively achieve the best fitness value through cost calculation and to validate the results of objective functions on 15 engineering benchmark problems with constraints. The water cycle algorithm (WCA), a hydrology-based method, provides global search locations based on the flow of streams and rivers toward the sea using predefined control parameters to generate a population matrix. A convergence plot for OCWCA compared to WCA demonstrates significant improvement in results, incorporating learnings from the WCA method and yielding the best fitness data.

关键词： Constraint-based optimization water cycle algorithm opposition-based learning chaos-based learning engineering problem

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A Modified water cycle algorithm: An Opposition Based Meta-Heuristic Optimization to Solve Real World Engineering Problems

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GAZI UNIVERSITY JOURNAL OF SCIENCE 2024年第3期37卷 1215-1234页

作者： Datta, Monalisa Sarkar, Dipu Das, Soumyabrata NIT Nagaland Dept Elect & Elect Engn Dimapur 797103 Chumukedima India Techno Int Dept Elect Engn Kolkata 700156 India Visvesvaraya Natl Inst Technol Elect Engn Dept Nagpur 440010 Maharashtra India

This paper proposes the Opposition based learning on a latest recent population based water cycle algorithm on different benchmark constraint optimization techniques. water cycle is a Hydrological based technique which works on better search location of the stream and river that flows to the sea which works on certain control parameters that will be defined initially and obtain the population matrix. With the help of the application of the opposition learning opposite search will be made to receive the better search location to find the better fitness value and avoid the premature convergence and get best convergence rate. This Proposed Opposition based water cycle algorithm is implemented and tested on fifteen benchmark problems mentioning the fitness value as well as the constraints value. The convergence plot using a comparative study between water cycle algorithm and Opposition based water cycle algorithm, the proposed method had proved to obtain the best result and superior for the problems on to which it had implemented. The ANOVA test result is shown for the statistical analysis of the data obtained.

关键词： Problems on benchmark water cycle algorithm Optimization design Opposition learning ANOVA test

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A water cycle algorithm based on quadratic interpolation for high-dimensional global optimization problems

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APPLIED INTELLIGENCE 2023年第3期53卷 2825-2849页

作者： Ye, Jiahao Xie, Lirong Wang, Hongwei Xinjiang Univ Sch Elect Engn Urumqi 830047 Xinjiang Peoples R China Dalian Univ Technol Sch Control Sci & Engn Dalian 116024 Liaoning Peoples R China

The water cycle algorithm (WCA) is easily trapped in local optimal solutions when dealing with high-dimensional optimization problems and has low precision and slow convergence. A WCA based on quadratic interpolation (QIWCA) is proposed in this study to address these drawbacks. First, a new nonlinear adjustment strategy for distance control parameters is designed to balance the exploration and exploitation capabilities of the algorithm. Second, during the search process of the algorithm, mutation operations are probabilistically performed to enhance the global exploration capability of the algorithm. Lastly, the quadratic interpolation operator is introduced to improve the local exploitation capability of the algorithm. QIWCA is also compared with several of the most advanced meta-heuristic algorithms on 46 benchmark functions. Experimental results show that QIWCA outperforms the compared algorithms in terms of convergence speed, global exploration capability, solution accuracy, and reliability.

关键词： water cycle algorithm Quadratic interpolation Global optimization High-dimensional optimization

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Optimization of irrigation management and environmental assessment using the water cycle algorithm

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SOIL USE AND MANAGEMENT 2023年第2期39卷 917-932页

作者： Rafiee, Mohammad Rafie Mahmoodi-Eshkaftaki, Mahmood Jahrom Univ Dept Water Sci & Engn Jahrom Iran Jahrom Univ Dept Mech Engn Biosyst Jahrom Iran Jahrom Univ Dept Mech Engn Biosyst POB 74135-111 Jahrom Iran

Obtaining high crop yields with limited water consumption requires optimal irrigation strategies based on comprehensive studies of the parameters of plant-environment interactions. Here, we used a structural equation modelling (SEM) to assess the relationships among input irrigation factors and moderate factors to find an optimum water use efficiency (WUE) response factor, for outdoor and greenhouse cultivation of eggplant (Solanum melongena). The input irrigation factors (including irrigation interval, water salinity and environment) and the moderate factors (evapotranspiration, soil salinity, plant parameters, fruit parameters and crop yield) were used in water cycle algorithm (WCA) and genetic algorithm (GA) methods to optimize the water use efficiency. The optimization process included finding the best combination of irrigation factors and optimized eggplant cultivation. The structural equation modelling results indicate that irrigation interval negatively affected water use efficiency with a more dominant effect on plant parameters. water salinity negatively affected the water use efficiency with a more dominant effect on soil salinity, crop yield and fruit parameters. Low salinity water was more effective than full irrigation to optimize the water use efficiency. The water cycle algorithm revealed that for outdoor cultivation, the optimal range of irrigation interval was 2-5 days and water salinity in the range of 0.8-2.2 ds/m. These factors optimized evapotranspiration (346.23-738.19 mm), soil salinity (4.16-9.45 ds/m), fruit parameters (33.81-35.12 cm) and crop yield (1715.7-2190.8 g/plant), as well as increasing the water use efficiency (3.08-4.89 g/(plant-mm)). Both the water cycle algorithm and genetic algorithm yielded very close to optimal values. Two years of repeated experiments and the closeness of the optimal values using the algorithms confirmed that the optimal amounts are reliable.

关键词： evapotranspiration irrigation management structural equation modelling water cycle algorithm water use efficiency

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Grayscale Image Enhancement Using water cycle algorithm

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IEEE ACCESS 2023年 11卷 86575-86596页

作者： Woldamanuel, Eyob Mersha Haramaya Univ Haramaya Inst Technol Sch Elect & Comp Engn Dire Dawa Ethiopia

Recent developments in engineering and computer sciences have heightened the need for digital image enhancement. Most of the previously reported works, however, focused on image enhancement using classical methods like mathematical transformations and spatial and frequency-domain methods. Hence, recently, there has been an increasing interest in using nature-inspired optimization techniques for image processing purposes. The water cycle algorithm (WCA) is one of the nature-inspired algorithms (NIAs) that have gotten much attention in optimizing real-world engineering problems due to its appealing performance. However, to the best of the author's knowledge, little research has been undertaken on the WCA's image-enhancing capacity. Thus, this work is intended to offer a modified histogram equalization (HE) approach using WCA to enhance the contrast of an image and maintain its brightness. Besides, the proposed WCA-based image enhancement technique was compared to linear contrast stretching (LCS), HE and its modified versions, particle swarm optimization (PSO), and accelerated particle swarm optimization (APSO). In addition to the objective function fitness, 11 full reference (FR) image quality assessment (IQA) metrics were employed to evaluate image quality and compare performance. Experimental results showed that the suggested image enhancement technique exhibited better performance than others in enhancing dark grayscale images in terms of objective function fitness and perceptual visual IQA metrics like multi-scale structural similarity (MS-SSIM), information-weighted structural similarity (IW-SSIM), information-weighted mean squared error (IW-MSE), and information-weighted peak signal-to-noise ratio (IW-PSNR). The proposed method also demonstrated a faster convergence time to an optimum solution.

关键词： Grayscale image histogram equalization image edge detection image enhancement image quality assessment metrics nature-inspired algorithms water cycle algorithm

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SMES and TCSC Coordinated Strategy for Multi-area Multi-source System with water cycle algorithm Based 3DOF-PID Controller

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SMART SCIENCE 2023年第1期11卷 1-15页

作者： Kalyan, Ch Naga Sai Goud, B. Srikanth Reddy, Ch Rami Bajaj, Mohit Rao, G. Srinivasa Vasireddy Venkatadri Inst Technol Dept Elect & Elect Engn Guntur Andhra Pradesh India Anurag Coll Engn Dept Elect & Elect Engn Ghatkesar 501301 India Malla Reddy Engn Coll A Dept Elect & Elect Engn Secunderabad India Natl Inst Technol Delhi Dept Elect & Elect Engn New Delhi India CMR Coll Engn & Technol Dept Elect & Elect Engn Kandlakoya Medchal India

This paper attempted to assess the supremacy of designed higher-order degree of freedom (DOF) proportional(P)-integral(I)-derivative(D) (PID) (3DOF-PID) controller making use of a new meta-heuristic optimization approach of water cycle algorithm (WCA) in the study of load frequency control. For this, two test system models of dual area hydro-thermal system system and multiarea multisource systems are believed for investigative purposes. The investigation is performed by imparting the area-1 of test system models with a disturbance of 10% step load (10%SLP). Parameters of 3DOF-PID are rendered optimally over the index of integral square error. Efficacy of the presented 3DOF-PID regulator fine-tuned with WCA is demonstrated with other control schemes that have been implemented on the same test systems. Moreover, superconducting magnetic energy storage and Thyristor controlled series compensator territorial schema is implemented for the MSMA system for performance enhancement. Finally, the robustness of the presented approach is demonstrated through sensitivity analysis. [GRAPHICS]

关键词： 3DOF-PID controller water cycle algorithm 10%SLP LFC SMES-TCSC

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Solving unconstrained, constrained optimization and constrained engineering problems using reconfigured water cycle algorithm

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EVOLUTIONARY INTELLIGENCE 2023年第2期16卷 633-649页

作者： Eid, Heba F. Abraham, Ajith Al Azhar Univ Fac Sci Cairo Egypt MIR Labs Machine Intelligence Res Labs Auburn WA 98071 Australia Innopolis Univ Ctr Artificial Intelligence Innopolis Russia

water cycle algorithm (WCA) is a recent meta-heuristic algorithm presented to solve various optimization problems. WCA has received critical intrigued from researchers in different fields. Nevertheless, the search equation provided in WCA is not of adequate explorative behavior. In this study a reconfigured version of the WCA is proposed, the proposed algorithm is named as RWCA. So as to improve the exploration procedure, a new position update strategy is proposed by integrating cauchy operator and a greedy selection procedure. Furthermore, in order to promote the exploration-exploitation balance of the RWCA algorithm, a nonlinear controlling parameter is proposed. The performance of RWCA is exhibited on 19 unconstrained benchmark functions. Statistical analysis proves that, RWCA significantly improves the performance of basic WCA by providing better solution quality, faster convergence and stronger robustness. Moreover, RWCA has been used to solve five constrained numerical and three engineering application problems. Based on the experiments and comparative findings, RWCA illustrates the adequacy and effectiveness to solve various constrained problems;as well as its capability of providing promising and competitive results solving real-world challenging engineering problems.

关键词： water cycle algorithm Constrained optimization Constrained engineering problem

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