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Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

“…Therefore, the usage of a swarming robotic system is proposed. In this thesis, a simple framework and methodology in developing a bio-inspired algorithm for cooperative swarming robotic application has been developed. …”
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A calibration framework for swarming ASVs' system design by Zainal Abidin, Zulkifli

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An improved data classification framework based on fractional particle swarm optimization by Sherwani, Fahad

“…Furthermore, the proposed MOFPSO algorithm is hybridized with Back-Propagation (BP), Elman Recurrent Neural Networks (RNN) and Levenberg-Marquardt (LM) Artificial Neural Networks (ANNs) to propose an enhanced data classification framework, especially for data classification applications. …”
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Interacted Multiple Ant Colonies for Search Stagnation Problem by Aljanabi, Alaa Ismael

“…An analysis study of the stagnation behaviour shows that the proposed algorithmic framework suffers less from stagnation than other ACO algorithmic frameworks.…”
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A Wavelet-Based Particle Swarm Optimization Algorithm for Digital Image Watermarking by Jasni, Mohamad Zain, Tao, Hai, Ahmed, M. Masroor, Abdalla, Ahmed N., Jing, Wang

“…This paper proposes the application of Discrete Wavelet Transform (DWT) into image watermarking by using Particle Swarm Optimization (PSO) which is an evolutionary technique with the stochastic, population-based algorithm for solving this problem. …”
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Metaheuristic Algorithms and Neural Networks in Hydrology

“…This book summarizes the latest research and developments related to the application of nature-inspired metaheuristic algorithms coupled with artificial neural networks (ANNs) in hydrology. …”
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Multi-Agent Reinforcement Learning For Swarm Robots Formation by Bujang, Christina

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Hardware Software Partitioning Using Particle Swarm Optimization (PSO) In Image Processing Application by Tan, Jia Zheng

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A new swarm-based framework for handwritten authorship identification in forensic document analysis by Pratama, Satrya Fajri, Draman @ Muda, Azah Kamilah, Choo, Yun Huoy, Draman @ Muda, Noor Azilah

“…This chapter focuses on the integration of Swarm Optimized and Computationally Inexpensive Floating Selection (SOCIFS) feature selection technique into the proposed hybrid of Writer Identification framework and feature selection framework, namely Cheap Computational Cost Class Specific Swarm Sequential Selection (C4S4). …”
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Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

“…Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. …”
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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

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A New Swarm-Based Framework for Handwritten Authorship Identification in Forensic Document Analysis by Draman @ Muda, Azah Kamilah, Choo, Yun Huoy, Draman @ Muda, Noor Azilah

“…Pratama et al. and feature selection framework, namely Cheap Computational Cost Class-Specific Swarm Sequential Selection (C4S4). …”
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom by Masrom, Suraya

“…Evaluations of four different sets of applications that used the proposed implementation frameworks with dynamic parameterization have indicated the effectiveness of each tested algorithm in comparison to the single PSO and constant parameterization. …”
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A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization by Kassim, Azleena Mohd

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The quadriceps muscle of knee joint modelling using Hybrid Particle Swarm Optimization-Neural Network (PSO-NN) by Ahmad Kamaruddin, Saadi, Tolos, Siti Marponga, Hee, Pah Chin, Md Ghani, Nor Azura, Ramli, Norazan Mohamed, Mohamed Nasir, Noorhamizah, Ksm Kader, Babul Salam, Huq, Mohammad Saiful

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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…In order to fill this gap, this article proposes a novel framework for comparing various variants of variable length-searching meta-heuristic algorithms in the application of feature selection. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…In order to fill this gap, this article proposes a novel framework for comparing various variants of variable length-searching meta-heuristic algorithms in the application of feature selection. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Sara, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…In order to fill this gap, this article proposes a novel framework for comparing various variants of variable length-searching meta-heuristic algorithms in the application of feature selection. …”
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Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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