Autonomous Greenhouse Cultivation of Dwarf Tomato: Performance Evaluation of Intelligent Algorithms for Multiple-Sensor Feedback by Stef C. Maree, Pinglin Zhang, Bart M. van Marrewijk, Feije de Zwart, Monique Bijlaard, Silke Hemming

“…For an optimal strategy, however, it is essential that control algorithms properly account for crop responses, which requires appropriate sensors, reliable data, and accurate models. …”
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Stochastic Multiple Chaotic Local Search-Incorporated Gradient-Based Optimizer by Hang Yu, Yu Zhang, Pengxing Cai, Junyan Yi, Sheng Li, Shi Wang

“…Meanwhile, chaotic local search (CLS) is an efficient search strategy with randomicity and ergodicity, which is usually used to improve global optimization algorithms. Accordingly, we incorporate GBO with CLS to strengthen the ability of exploration and keep high-level population diversity for original GBO. …”
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Application of the joint clustering algorithm based on Gaussian kernels and differential privacy in lung cancer identification by Hang Yanping, Zheng Haixia, Yang Minmin, Wang Nan, Kong Miaomiao, Zhao Mingming

“…The algorithm enhances cancer detection while ensuring data privacy. …”
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Machine learning prediction of permeability distribution in the X field Malay Basin using elastic properties by Zaky Ahmad Riyadi, John Oluwadamilola Olutoki, Maman Hermana, Abdul Halim Abdul Latif, Ida Bagus Suananda Yogi, Said Jadid A. Kadir

“…Additionally, Tree-structured Parzen Estimator-Bayesian optimization method was utilized to optimize the machine learning model's hyperparameters and improve accuracy. …”
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Software-defined networking QoS optimization based on deep reinforcement learning by Julong LAN, Xueshuai ZHANG, Yuxiang HU, Penghao SUN

“…To solve the problem that the QoS optimization schemes which based on heuristic algorithm degraded often due to the mismatch between parameters and network characteristics in software-defined networking scenarios,a software-defined networking QoS optimization algorithm based on deep reinforcement learning was proposed.Firstly,the network resources and state information were integrated into the network model,and then the flow perception capability was improved by the long short-term memory,and finally the dynamic flow scheduling strategy,which satisfied the specific QoS objectives,were generated in combination with deep reinforcement learning.The experimental results show that,compared with the existing algorithms,the proposed algorithm not only ensures the end-to-end delay and packet loss rate,but also improves the network load balancing by 22.7% and increases the throughput by 8.2%.…”
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Advanced analytics to improve energy efficiency of steel industry - A systematic review on ladle logistics by Akhil Raja Keshetti, Victor S.P. Ruela, Hao Chen, Marcos R. Machado

“…The scientific landscape has State-of-the-Art optimiser algorithms built using mathematical models to generate ladle logistics schedules. …”
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Detection of capsaicin content by near-infrared spectroscopy combined with optimal wavelengths by LÜ Xiaohan, JIANG Jinlin, YANG Jing, CHEN Jianying, CEN Haiyan, FU Hongfei, ZHOU Yifei

“…In addition, compared with the full spectra of 200 wavelengths, the number of the optimal wavelengths selected by CARS was reduced by 96%, which indicated that optimal wavelengths can be used to simplify the models and improve the operation efficiency. …”
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Optimizing the strategy of new media content distribution using fuzzy logic by Jianhua Qi, Jing Lin

“…To solve this problem, this study proposes a new media content distribution strategy based on fuzzy logic optimization, aiming to improve the efficiency and user experience of the recommendation system. …”
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Optimization of Shift Strategy Based on Vehicle Mass and Road Gradient Estimation by Huijun Yue, Haobo Jing, Zhenkun Dai, Jinyu Lin, Zihan Ma, Changtong Zhao, Pan Zhang

“…The experiment verifies that the optimized shift strategy can effectively improve the dynamic performance of the vehicle. …”
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A Comparison of AutoML Hyperparameter Optimization Tools For Tabular Data by Prativa Pokhrel, Alina Lazar

“…Therefore, finding the optimal values of these hyperparameters is integral in improving the prediction accuracy of an ML algorithm and the model selection. …”
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Bi-Objective Optimization of Product Selection and Ranking Considering Sequential Search by Yuyang Tan, Hao Gong, Chunxiang Guo

“…To address this gap, we study a bi-objective product selection and ranking (BP-SS) problem considering sequential search, aiming to jointly optimize the expected revenue and market share. We first develop a two-stage choice model with consideration sets to capture how sequential search influences customer decision-making. …”
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Bayesian Optimization of insect trap distribution for pest monitoring efficiency in agroecosystems by Eric Yanchenko, Thomas M. Chappell, Anders S. Huseth

“…In this study, a Bayesian optimization (BO) algorithm was used to learn more about the optimal distribution of a fine-scale trap network targeting Helicoverpa zea (Boddie), a significant agricultural pest across North America. …”
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Tool wear monitoring method based on AMIDBOAB and imbalanced data optimization by Guan-Hua Xu, Hong-Yu Wu, Bo Tang, Jun-Long Xu

“…Introducing circle chaotic mapping, Levy flight strategy, and adaptive variable inertia weight, a multiple improvement dung beetle optimizer algorithm is proposed to optimize the parameters of the base classifier in the adaptive boosting model. …”
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Research of Real Time Optimization of Gear for DCT Vehicle Under the Ramp by Ding Hua, Xu Cong

“…The value of slope is identified based on the EKF algorithm and the dynamics model of ramp. On the basis of ramp identification model and traditional shift schedule,a real time online optimization of dual clutch transmission（ DCT） gear is presented based on fuzzy control method. …”
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Multi-Attribute Collaborative Optimization for Multimodal Transportation Based on User Preferences by Youpeng Lu, Gang Gao

“…In terms of solution methods, an improved Genetic Algorithm (GA) and Aptenodytes Forsteri Optimization (AFO) hybrid algorithm (GA-AFO) is proposed, which introduces GA to generate a high-quality initial population to accelerate convergence. …”
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Power Grid Clock Synchronization Optimization Based on Stackelberg Game Theory by Jiahao Li, Yitao Zhao, Yiming Zhang, Zhiyu Xia, Chuanxu Chen, Quansheng Guan

“…Then, a two-layer Stackedberg game model has emerged to achieve optimal bandwidth allocation in the network and improve clock synchronization accuracy. …”
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Multi-objective optimization of integrated energy system considering customer satisfaction by YU Wuyue, JIA Yuchen, HUO Limin, WEN Peng, GAO Liai

“…A multi-objective optimization function with improved customer satisfaction, economy and carbon emission is constructed, and MAPSO (multi-group adaptive particle swarm optimization) algorithm is used for optimization analysis, and the Pareto optimal frontier solution sets in different scenarios are obtained. …”
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Two-grid mixed finite element method combined with the BDF2-θ for a two-dimensional nonlinear fractional pseudo-hyperbolic wave equation by Yan Wang, Yining Yang, Nian Wang, Hong Li, Yang Liu

“…In this article, a fast two-grid mixed finite element (T-GMFE) algorithm based on a time second-order discrete scheme with parameter θ is considered to numerically solve a class of two-dimensional nonlinear fractional pseudo-hyperbolic wave models. …”
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Improving the Integrity of a Voting Process with Biometric Authentication and Data Encryption by Walter M. Molina, Lino R. Mac Kay, Daniel Subauste

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Optimization Research of the Hinge Position and Output Speed of Electromechanical Erection Device by Wei Cai, Shangjun Ma, Jianxin Zhang, Yong Zhou, Xiang Chen, Geng Liu

“…In order to realize the fast erection of electromechanical actuator， and the influence rule of the hinge position and output speed on output power and force in erection device is revealed， the hinge position and the output speed of the system are optimized and researched. The kinetics models of load and electromechanical actuator are found respectively. …”
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