Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction. by Ruiyu Zhan

“…To tackle this issue, we present an innovative method that harmonizes the Grey Wolf Optimizer (GWO) with Levy flight to optimize the weights and biases of a Backpropagation (BP) neural network-a prominent machine learning model extensively employed in classification tasks. …”
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Secondary throughput maximization scheme for non-linear energy harvesting cognitive radio networks by Haijiang GE, Ning JIA, Kaikai CHI, Yunzhi CHEN

“…Aiming at a cognitive radio network (CRN) consisting of a pair of primary users and M pairs of secondary users, the secondary throughput maximization for CRN based on the non-linear energy harvesting model was studied.Specifically, in the case of considering secondary transmitter (ST) circuit power, the secondary throughput maximization (STM) problem with primary users’ throughput demands was first modeled as a non-linear optimization problem and then transformed into a convex optimization problem.Finally, a low-complexity algorithm combining the golden section and dichotomy was proposed.By applying this low-complexity algorithm, the optimal time allocation of the primary transmitter (PT)’s energy transmission and secondary users’ information transmission, and the optimal transmission power of PT were obtained.In addition, for the case of neglecting the ST circuit power, the convex property of the STM problem was first proved, and then a more efficient algorithm was designed to solve it.The simulation results show that compared with the equal time allocation method and the link gain priority method, the proposed design algorithm significantly improves the throughput of secondary users.…”
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A novel mechanism-guided residual network for accurate modelling of scroll expander under noisy and sparse data conditions by Xiaoshuang Lv, Xin Ma, Wei Peng, Ke Li, Chengdong Li

“…This framework is based on the architecture of residual network, where the mechanistic laws are embedded as constraints in the training of the network through an improved loss function. Then, a hybrid optimization algorithm is detailed, which can achieve efficient and accurate updating of the parameters of the network and mechanistic equations. …”
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Research on computer multi feature fusion SVM model based on remote sensing image recognition and low energy system by Yangming Wu, Hao Wu, Xin Tang, Jianwei Lv, Rufei Zhang

“…Aiming at the limitations of the traditional SVM model in processing high-dimensional data, an optimization algorithm is designed to reduce the computational complexity and improve the recognition accuracy of the model through dimensionality reduction and feature selection. …”
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Autonomous Dogfight Decision-Making for Air Combat Based on Reinforcement Learning with Automatic Opponent Sampling by Can Chen, Tao Song, Li Mo, Maolong Lv, Defu Lin

“…The training outcomes demonstrate that this improved PPO algorithm with an AOS framework outperforms existing reinforcement learning methods such as the soft actor–critic (SAC) algorithm and the PPO algorithm with prioritized fictitious self-play (PFSP). …”
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探討強化學習演算法之素材推薦機制與AI學習履歷之學習者感知 Learner Perceptions of AI-Powered Learning Portfolios and Personalized Material Recommendation Mechanisms in Reinforcement Learning Algorithms... by 曾建維 Jian-Wei Tzeng, 黃天麒 Tien-Chi Huang, 薛承祐 Cheng-Yu Hsueh, 廖英淞 Ying-Song Liao

“…Enhancing usage incentive, continuously refining the accuracy of the recommendation system’s algorithms, and conducting comparative analyses with existing systems are essential to improve the recommendation system’s perceived utility. …”
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An Innovative Online Adaptive High-Efficiency Controller for Micro Gas Turbine: Design and Simulation Validation by Rui Yang, Yongbao Liu, Xing He, Zhimeng Liu

“…When the DL_ELM model detects a gas turbine’s performance change, a particle swarm optimization (PSO) algorithm is employed to iteratively calculate the DFF_DL_OSELM model, determining the optimal speed control scheme to ensure the gas turbine operates at maximum efficiency. …”
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Advancing named entity recognition in interprofessional collaboration and education by Rui Zhang, Yifeng Shan, MengZhe Zhen

“…Existing approaches lack adaptability to evolving terminologies and insufficiently address the complex interaction dynamics inherent in multi-disciplinary frameworks.MethodsTo address these limitations, we propose a Synergistic Collaboration Framework (SCF) integrated with an Adaptive Synergy Optimization Strategy (ASOS). SCF models IPC as a dynamic multi-agent system, where disciplines are represented as intelligent agents interacting within a weighted graph structure. …”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…This study presents an enhanced deep learning model designed to improve the accuracy and adaptability of recognition algorithms for robotic arm-based harvesting. …”
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Thermal Error Prediction in High-Power Grinding Motorized Spindles for Computer Numerical Control Machining Based on Data-Driven Methods by Quanhui Wu, Yafeng Li, Zhengfu Lin, Baisong Pan, Dawei Gu, Hailin Luo

“…The subsequent problem of thermal error compensation can be effectively solved by a suitable thermal error model, which is crucial for improving the machining accuracy of the actual machining process. …”
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IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition by Mashael Maashi, Huda G. Iskandar, Mohammed Rizwanullah

“…Finally, the attraction-repulsion optimization algorithm (AROA) adjusts the hyperparameter values of the CNN-BiGRU-A method optimally, resulting in more excellent classification performance. …”
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RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…These methods have high computational costs and are not efficient for real-time applications.MethodsTo address these issues, this paper presents a Quantum-behaved Particle Swarm Optimization model enhanced by deep reinforcement learning (RL-QPSO Net) aimed at improving global optimality and adaptability in path planning. …”
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Meteorological data implications modeling on evapotranspiration variability in arid and semi-arid zones in Saudi Arabia using hybrid metaheuristic by Oulad Naoui Noureddine, Sekkoum Mohamed, Cherif El Amine, Ali Alzaed, Meseret Abeje Gedfew, Sherif S. M. Ghoneim, Enas E. Hussein

“…In this paper, the Bat algorithm (BAT) with the Newton Method (NM), Bird Swarm Algorithm (BSA), Genetic Algorithm (GA), and Chicken Swarm Optimization Algorithm (CSO) are used as a hybrid model in arid and semi-arid zones in Saudi Arabia as well as for modeling rainfall, temperature, and solar radiation implications on evapotranspiration variability. …”
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Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means by Bo Li, Guochao Qian, Lijun Tang, Peng Sun, Zhensheng Wu

“…Firstly, the DBPSO algorithm is used to optimize the configuration scheme of the distributed voltage and current sensing device, which reduces the number of measuring devices and system cost on the premise of ensuring the global observability of the distribution network. …”
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Phytoplanktonic Photoacclimation Under Clouds by Charlotte Begouen Demeaux, Emmanuel Boss, Jason R. Graff, Michael J. Behrenfeld, Toby K. Westberry

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Exploiting full-duplex opportunities in WLANs via a reinforcement learning-based medium access control protocol by Song Liu, Peng Wei

“…Thus, we develop a Window-Constraint Bayesian (WCB) algorithm to generate optimized scheduling policies online. …”
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A single-snapshot inverse solver for two-species graph model of tau pathology spreading in human Alzheimer’s disease by Zheyu Wen, Ali Ghafouri, George Biros, the Alzheimer’s Disease Neuroimaging Initiative (ADNI)

“…This optimization problem is solved with a projection-based quasi-Newton algorithm. …”
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A Developed Mathematical Model for Designing a Multilevel Sustainable Supply Chain Network Taking into Account Environmental Decisions by Mehrab Paydarfard, Roya Pirzadeh, Ali Ahmadi, Masoud Zohrabi, Farkhondeh Mortaz Hejri, Malek Hasan

“…In addition, the proposed model was optimized by the whale optimization algorithm (WOA) to find the best solution in large-scale instances in a short and reasonable time. …”
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Robust model predictive control for polytopic uncertain systems via a high-rate network with the FlexRay protocol by Jianhua Wang, Fuqiang Fan, Yanye Yu, Shuxin Du, Xiaorui Guo

“…Subsequently, taking both high-rate networks and FRP into account, sufficient conditions are obtained by solving a time-varying terminal constraint set of an auxiliary optimization problem. In addition, an algorithm including both off-line and on-line parts is provided to find a sub-optimal solution. …”
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Physically-constrained evapotranspiration models with machine learning parameterization outperform pure machine learning: Critical role of domain knowledge. by Yeonuk Kim, Monica Garcia, T Andrew Black, Mark S Johnson

“…All models employed the random forest algorithm and were trained on daily-scale ET observations, in-situ meteorological data and satellite remote sensing. …”
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