Flexible manipulator trajectory tracking based on an improved adaptive particle swarm optimization algorithm with fuzzy PD control by W. Sun, Y. Jin, K. Dai, Z. Guo, F. Ma

“…To address these challenges and improve the trajectory tracking performance of the manipulator, this paper focused on vibration suppression and trajectory planning for a two-link flexible manipulator and proposed a novel control method that integrates a modified adaptive particle swarm optimization algorithm (MAPSO) with fuzzy proportional–derivative (PD) control to achieve effective trajectory tracking. …”
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Optimization of Time-Varying Temperature Profiles for Enhanced Beer Fermentation by Evolutive Algorithms by Pablo Ruarte, Nadia Pantano, Marianela Noriega, Cecilia Fernández, Emanuel Serrano, Gustavo Scaglia

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Robust DWT-HMM image watermarking algorithm optimized with content-adaptive approach by WANG Chun-tao1, NI Jiang-qun1, HUANG Ji-wu1, ZHANG Rong-yue1, LUO Xi-zhang1

“…A robust watermarking algorithm based on content-adaptive approach was proposed to optimize the tradeoff between robustness and imperceptibility,which was characterized as follows: the entropy masking proposed by Watson etc.was constructed in wavelet domain,which was then used to constitute the integrated HVS model;three different measures,namely,energy,entropy and integrated HVS,for content-adaptive selection were constructed and investigated;repeat-accumulate（RA） code with erasure and error correction was used to tackle the synchronization issue of the exact positions for watermark embedding;and a posteriori DWT-HMM detector was utilized for watermark detection.Simula-tion results show that the proposed content-adaptive watermarking algorithm,under the same imperceptibility,has con-siderable improvement in robustness performance over the traditional one with stochastic approach.…”
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A study of scheduling strategies for microgrids based on the non-dominated sorting dung beetle optimization algorithm by Yutong Chen, Wu Ning, Wei Du

“…Specifically, compared with the Grey Wolf Optimizer (GWO) and the standard Dung Beetle Optimization (DBO) algorithm, the overall operation cost of NSDBO is reduced by 52% and 8.1%, respectively. …”
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Multi-objective optimization of sustainable cement-zeolite improved sand based on life cycle assessment and artificial intelligence [version 1; peer review: 1 approved, 2 approved... by Hossein MolaAbasi, Satinder Kaur Brar, Amin Tanhadoust, Sepideh Nasrollahpour, Omolbanin Ataee, Moncef L. Nehdi

“…Through a tuning process, the BPNN model found the optimal architecture and accurately predicted the unconfined compressive strength of cement-zeolite improved sand systems. …”
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Analysis of algorithms of interference coding and improving the efficiency in the complex systems by Oleg Pavlovich Malofey, Alexander Olegovych Malofey, Anastasia Evgenievna Shangina

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Combining Transfer Learning and Ensemble Algorithms for Improved Citrus Leaf Disease Classification by Hongyan Zhu, Dani Wang, Yuzhen Wei, Xuran Zhang, Lin Li

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Hybrid genetic algorithm to minimize scheduling cost with unequal and job dependent earliness tardiness cost by Prasad Bari, Prasad Karande, Vaidehi Bag

“…This article presents two combinatorial genetic algorithms (GA), unequal earliness tardiness-GA (UET-GA) and job-dependent earliness tardiness-GA (JDET-GA) for the single-machine scheduling problem to minimize earliness tardiness (ET) cost. …”
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GC-Faster RCNN: The Object Detection Algorithm for Agricultural Pests Based on Improved Hybrid Attention Mechanism by Bolun Guan, Yaqian Wu, Jingbo Zhu, Juanjuan Kong, Wei Dong

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Enhancing HEVC Efficiency: A Novel Approach to Intra-Mode Estimation Through Hadamard Cost Analysis by Junaid Tariq, Imran Javed, Touseef Sadiq, Hameedur Rahman, Ashfaq Hussain Farooqi, Amir Ijaz

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Improved Correlation of Oil Recovery Factor for Water Driven Reservoirs in the Niger Delta by Ayodele Daniel, Faisal Olasubomi Olanipekun, Sunday Oloruntoba Isehunwa

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Improved gated recurrent unit-based osteosarcoma prediction on histology images: a meta-heuristic-oriented optimization concept by S. Prabakaran, S. Mary Praveena

“…These extracted features undergo the final prediction phase that is accomplished by the novel improved recurrent gated recurrent unit (IGRU), in which the parameter tuning of GRU is accomplished by the osprey optimization algorithm (OOA) with the consideration of error minimization as the major objective function. …”
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Orga-Dete: An Improved Lightweight Deep Learning Model for Lung Organoid Detection and Classification by Xuan Huang, Qin Gao, Hanwen Zhang, Fuhong Min, Dong Li, Gangyin Luo

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Improved artificial protozoa optimizer: A new method for solar photovoltaic parameter estimation by Wenhao Lai, Duoduo Liu, Jialong Yang, Lei Guo, Weijin Qian, Jiaojiao Wu, Haifeng Zhou

“…The accuracy of parameters in solar cell models is helpful for optimizing the maximum power point tracking, which allows for an improvement in power generation efficiency. …”
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Unobtrusive Sleep Posture Detection Using a Smart Bed Mattress with Optimally Distributed Triaxial Accelerometer Array and Parallel Convolutional Spatiotemporal Network by Zhuofu Liu, Gaohan Li, Chuanyi Wang, Vincenzo Cascioli, Peter W. McCarthy

“…For sleep posture classification, we employ an improved density peak clustering algorithm that incorporates the K-nearest neighbor mechanism. …”
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Passive Drag Reduction Optimization for Complex Commercial Vehicle Models by G. Liao, M. Xue, L. Yue, H. Yang, P. Guo, X. Hu, Z. Wang, T. Ma

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An Energy Management Optimization Strategy for Regional Power Grid Energy Storage System Based on Improved Artificial Bee Colony Algorithm by Ziqi WANG, Huiyuan ZHANG, Jun XU, Jiehui CHENG

“…Simulation results show that the energy management optimization of energy storage can improve the overall economic benefits, and the improved artificial bee colony algorithm has good global search ability and convergence.…”
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Distributed data trading algorithm based on multi-objective utility optimization by Xiaohong HUANG, Yong ZHANG, Desheng SHAN, Yekui QIAN, Lu HAN, Dandan LI, Qun CONG

“…The traditional centralized data trading models are not well applicable to the current intelligent era where everything is interconnected and real-time data is generated, and in order to maximize the use of collected data, it is essential to design an effective data trading framework.Therefore, a distributed data trading framework based on consortium blockchain was proposed, which realized P2P data trading without relying on a third party.Aiming at the problem that existing data trading models only consider the factors of the data itself and ignore the factors related to user tasks, a bi-level multi-objective optimization model was constructed based on multi-dimensional factors, such as data quality, data attributes, attribute relevance and consumer competition, to optimize the utilities of data provider (DP) and data consumer (DC).To solve the above model, an improved multi-objective genetic algorithm-collaborative NSGAII was proposed, calculated by the cooperation of DP, DC and data aggregator (AG).The simulation results show that the collaborative NSGAII achieves better performance in terms of the utilities of DP and DC, thus realizing more effective data trading.…”
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Real-Time Recognition and Localization of Kiwifruit Based on Improved YOLOv5s Algorithm by Jin-Sui Dai, Zhi-Qin He

“…First, data enhancement is implemented in the training strategy to ensure the model’s efficient learning and generalization ability in complex environments; then the Coordinate Attention mechanism is introduced to highlight the key features of the image and improve detail detection; Secondly, the Bidirectional Feature Pyramid Network structure is used to optimize the feature fusion and strengthen the information exchange between different layers through bidirectional connectivity; then, the loss function is optimized to improve the bounding box localization accuracy; and finally, the combined with the binocular vision stereo matching algorithm Semi-Global Block Matching to obtain the spatial location information of Kiwifruit. …”
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Enhanced futures price-spread forecasting based on an attention-driven optimized LSTM network: integrating an improved grey wolf optimizer algorithm for enhanced accuracy by Yongli Tang, Zhenlun Gao, Zhongqi Cai, Jinxia Yu, Panke Qin

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