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Relevant bibliographies by topics / WOA-BAT

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Academic literature on the topic 'WOA-BAT'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "WOA-BAT"

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Mohammed, Hardi M., Shahla U. Umar, and Tarik A. Rashid. "A Systematic and Meta-Analysis Survey of Whale Optimization Algorithm." Computational Intelligence and Neuroscience 2019 (April 28, 2019): 1–25. http://dx.doi.org/10.1155/2019/8718571.

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The whale optimization algorithm (WOA) is a nature-inspired metaheuristic optimization algorithm, which was proposed by Mirjalili and Lewis in 2016. This algorithm has shown its ability to solve many problems. Comprehensive surveys have been conducted about some other nature-inspired algorithms, such as ABC and PSO. Nonetheless, no survey search work has been conducted on WOA. Therefore, in this paper, a systematic and meta-analysis survey of WOA is conducted to help researchers to use it in different areas or hybridize it with other common algorithms. Thus, WOA is presented in depth in terms

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Hidayat, Nur Wahyu, Purwanto, and Fikri Budiman. "Whale Optimization Algorithm Bat Chaotic Map Multi Frekuensi for Finding Optimum Value." Journal of Applied Intelligent System 5, no. 2 (2021): 80–90. http://dx.doi.org/10.33633/jais.v5i2.4432.

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Optimization is one of the most interesting things in life. Metaheuristic is a method of optimization that tries to balance randomization and local search. Whale Optimization Algorithm (WOA) is a metaheuristic method that is inspired by the hunting behavior of humpback whales. WOA is very competitive compared to other metaheuristic algorithms, but WOA is easily trapped in a local optimum due to the use of encircling mechanism in its search space resulting in low performance. In this research, the WOA algorithm is combined with the BAT chaotic map multi-frequency (BCM) algorithm. This method is

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3

Dutta, Sayantan, and Ayan Banerjee. "Highly Precise Modified Blue Whale Method Framed by Blending Bat and Local Search Algorithm for the Optimality of Image Fusion Algorithm." December 2020 2, no. 4 (2020): 195–208. http://dx.doi.org/10.36548/jscp.2020.4.001.

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Image fusion has gained huge popularity in the field of medical and satellite imaging for image analysis. The lack of usages of image fusion is due to a deficiency of suitable optimization techniques and dedicated hardware. In recent days WOA (whale optimization algorithm) is gaining popularity. Like another straightforward nature-inspired algorithm, WOA has some problems in its searching process. In this paper, we have tried to improve the WOA algorithm by modifying the WOA algorithm. This MWOA (modified whale optimization algorithm) algorithm is amalgamed with LSA (local search algorithm) an

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Kanagaraj, Ganesan, SAR Sheik Masthan, and Vincent F. Yu. "Meta-Heuristics Based Inverse Kinematics of Robot Manipulator’s Path Tracking Capability Under Joint Limits." MENDEL 28, no. 1 (2022): 41–54. http://dx.doi.org/10.13164/mendel.2022.1.041.

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In robot-assisted manufacturing or assembly, following a predefined path became a critical aspect. In general, inverse kinematics offers the solution to control the movement of manipulator while following the trajectory. The main problem with the inverse kinematics approach is that inverse kinematics are computationally complex. For a redundant manipulator, this complexity is further increased. Instead of employing inverse kinematics, the complexity can be reduced by using a heuristic algorithm. Therefore, a heuristic-based approach can be used to solve the inverse kinematics of the robot mani

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Saoud, Afaf, and Abdelmadjid Recioui. "Hybrid algorithm for cloud-fog system based load balancing in smart grids." Bulletin of Electrical Engineering and Informatics 11, no. 1 (2022): 477–87. http://dx.doi.org/10.11591/eei.v11i1.3450.

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Energy management is among the key components of smart metering. Its role is to balance energy consumption and distribution. Smart devices integration results in a huge data exchange between different parts of the smart grid causing a delay in the response and processing time. To overcome this latency issue, the cloud computing has been proposed. However, cloud computing does not perform well when there are large distances from the cloud to the consumers. Fog computing solves this issue. In this paper, a cloud-fog computing system is presented to achieve an accurate load balancing. The hybridi

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Afaf, Saoud, and Recioui Abdelmadjid. "Hybrid algorithm for cloud-fog system based load balancing in smart grids." Bulletin of Electrical Engineering and Informatics 11, no. 1 (2022): 477–87. https://doi.org/10.11591/eei.v11i1.3450.

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Energy management is among the key components of smart metering. Its role is to balance energy consumption and distribution. Smart devices integration results in a huge data exchange between different parts of the smart grid causing a delay in the response and processing time. To overcome this latency issue, the cloud computing has been proposed. However, cloud computing does not perform well when there are large distances from the cloud to the consumers. Fog computing solves this issue. In this paper, a cloud-fog computing system is presented to achieve an accurate load balancing. The hybridi

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Flayyih, Kadhim Hayyawi, and Mohsen Nickray. "Energy-efficient clustering in wireless sensor networks using metaheuristic algorithms." Edelweiss Applied Science and Technology 8, no. 6 (2024): 8582–610. https://doi.org/10.55214/25768484.v8i6.3848.

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Energy management in Wireless Sensor Networks (WSNs) remains a critical challenge, particularly in clustering processes. This article compares three optimization algorithms—Grasshopper Optimization Algorithm (GOA), Bat Algorithm (BA), and Whale Optimization Algorithm (WOA)—to achieve energy-efficient clustering and extend network lifetime. Initial cluster head placement is performed using K-means clustering, and a novel cost function is introduced that considers energy consumption and node distribution, enhancing the network’s efficiency and resilience. The algorithms are evaluated across thre

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Sungheetha, Akey, and Rajesh Sharma R. "Fuzzy Chaos Whale Optimization and BAT Integrated Algorithm for Parameter Estimation in Sewage Treatment." March 2021 3, no. 1 (2021): 10–18. http://dx.doi.org/10.36548/jscp.2021.1.002.

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Biological and social issues rise with faults that occur in waste water treatment plant (WWTP). Nature as well as humans are negatively impacted by the dangerous effects of poorly treated wastewater. This paper combines the fuzzy logic, chaos theory, whale optimization algorithm (WOA) and BAT algorithm (FCW-BAT) to create a novel model for parameter estimation. The WWTP applications are exposed to FCW-BAT algorithm for identifying non-well-structured domain, validating decision rules, cost reduction and estimation of several relevant attributes from the complete dataset. The significant data i

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Mohammed, Hardi M., Zrar Kh Abdul, Tarik A. Rashid, Abeer Alsadoon, and Nebojsa Bacanin. "A new K-means grey wolf algorithm for engineering problems." World Journal of Engineering 18, no. 4 (2021): 630–38. http://dx.doi.org/10.1108/wje-10-2020-0527.

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Purpose This paper aims at studying meta-heuristic algorithms. One of the common meta-heuristic optimization algorithms is called grey wolf optimization (GWO). The key aim is to enhance the limitations of the wolves’ searching process of attacking gray wolves. Design/methodology/approach The development of meta-heuristic algorithms has increased by researchers to use them extensively in the field of business, science and engineering. In this paper, the K-means clustering algorithm is used to enhance the performance of the original GWO; the new algorithm is called K-means clustering gray wolf o

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Et.al, Rozlini Mohamed. "An Optimized DiscretizationApproach using k-Means Bat Algorithm." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 1842–51. http://dx.doi.org/10.17762/turcomat.v12i3.1013.

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This study has proposed arelatively new discretization approach using k-means and Bat algorithm in preparation phase of classification problem. In essence, bat algorithm is applied to find the best search space solution. Eventually, the best search space solution is utilized to produce cluster centroid. The cluster centroid is very useful to determine appropriate breakpoint for discretization. The proposed discretization approach is applied in the experiments with continuous datasets. Decision Tree, k-Nearest Neighbours and Naïve Bayes classifiers are used in the experiments. The proposed disc

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Book chapters on the topic "WOA-BAT"

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Laiju, Noel Jose Thengappurackal, Reza Sedaghat, and Prathap Siddavaatam. "Novel Hybrid GWO-WOA and BAT-PSO Algorithms for Solving Design Optimization Problems." In Transactions on Computational Science XXXVIII. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-63170-6_7.

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Parvathala, Balakesava Reddy, A. Manikandan, P. Vijayalakshmi, M. Muzammil Parvez, S. Harihara Gopalan, and S. Ramalingam. "Bio-Inspired Metaheuristic Algorithm for Network Intrusion Detection System of Architecture." In Bio-Inspired Intelligence for Smart Decision-Making. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5276-2.ch004.

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By identifying different kinds of attacks and application misuse that firewalls normally aren't able to identify, network intrusion detection systems (IDS) are intended to keep computer networks safe. When creating a network intrusion detection system, feature selection techniques are crucial. Several bionic meta-heuristic algorithms are used to quickly categorize network traffic as problematic or normal, then decrease features to demonstrate higher accuracy. Thus, in order to detect frequent attacks, this research proposes a hybrid model of network intrusion detection system (IDS) based on an

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Qasim, Mohammad, Mohammad Sajid, Ranjit Rajak, and Mohammad Shahid. "Task Scheduling Strategy Using Chaotic Whale Optimization Algorithm in Cloud Computing." In Advances in Computer and Electrical Engineering. IGI Global, 2024. https://doi.org/10.4018/979-8-3693-6834-3.ch002.

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Cloud computing is becoming popular because it can provide cloud consumers with IT services scaled up globally over the internet. These services include platforms, applications, and infrastructure. Moreover, cloud computing can be provided on demand and offered in different pricing packages. To schedule the task optimally in a cloud environment is considered an NP-hard problem, which has become complex with the introduction of variables such as resource dynamicity and on-demand consumer applications. The proposed research introduces a Whale Optimization Algorithm (WOA) incorporating a transfer

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