Bacterial Foraging-Tabu Search Metaheuristics for Identification of Nonlinear Friction Model by Nuapett Sarasiri, Kittiwong Suthamno, Sarawut Sujitjorn

“…The proposed cooperative algorithms are formed from the bacterial foraging optimization (BFO) algorithm and the tabu search (TS). …”
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Differentiable Few-view CT-Reconstruction for Arbitrary CT-Trajectories including Prior Knowledge by Linda-Sophie Schneider, Adrian Waldyra, Yipeng Sun, Andreas K. Maier

“…This paper presents a novel two-step pipeline for few-view CT reconstruction that combines discrete prior generation with differentiable optimization. First, the Discrete Algebraic Reconstruction Technique generates a binary volume that provides robust prior information about the object’s structure. …”
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Efficient Method for Aeroelastic Tailoring of Composite Wing to Minimize Gust Response by Yang Yu, Zhengjie Wang, Shijun Guo

“…The computational time of the optimization process has been reduced by 90% at the cost of accuracy reduction of 2~4% comparing with the traditional dynamic response analysis.…”
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Intelligent System of Somatosensory Music Therapy Information Feedback in Deep Learning Environment by Nan Zhao

“…Through continuous adjustment and optimization of the weight matrix in the model, a stable recognition model is obtained. …”
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A Novel Mining Approach for Data Analysis and Processing Using Unmanned Aerial Vehicles by Ali Alenezi, Ahmad Sawalmeh, Hazim Shakhatreh, Muhannad Almutiry, Nasser Aedh Alreshidi

“…Because the problem is non-convex, the particle swarm optimization algorithm is used to solve it and determine an efficient location and trajectory of the UAV.…”
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Energy Efficiency Adaptation for Multihop Routing in Wireless Sensor Networks by Abdellah Chehri, Hussein T. Mouftah

“…In this paper we use an optimization scheme based on adaptive modulation and power control for a green routing protocol. …”
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s-Goodness for Low-Rank Matrix Recovery by Lingchen Kong, Levent Tunçel, Naihua Xiu

“…Low-rank matrix recovery (LMR) is a rank minimization problem subject to linear equality constraints, and it arises in many fields such as signal and image processing, statistics, computer vision, and system identification and control. This class of optimization problems is generally 𝒩𝒫 hard. A popular approach replaces the rank function with the nuclear norm of the matrix variable. …”
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Multiobjective Day-Ahead Scheduling of Reconfigurable-Based Microgrids Through Electric Vehicles and Demand Response Integration by Ali Mirzaei, Navid Taghizadegan Kalantari, Sajad Najafi Ravadanegh

“…Because of these two compromising objectives, the evolutionary multiobjective seagull optimization algorithm is utilized to find the best local solutions. …”
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A computing allocation strategy for Internet of things’ resources based on edge computing by Zengrong Zhang

“…First, based on the comprehensive consideration of computing resources, bandwidth, and migration decisions, an optimization problem is constructed that minimizes the sum of all user task execution delays and energy consumption weights. …”
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Scilab-RL: A software framework for efficient reinforcement learning and cognitive modeling research by Jan Benad, Frank Röder, Manfred Eppe

“…It enables native possibilities for experiment visualizations and hyperparameter optimization. We describe how these features enable researchers to conduct experiments with minimal time effort, thus maximizing research output.…”
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Parameter Extraction of Solar Photovoltaic Modules Using Gravitational Search Algorithm by R. Sarjila, K. Ravi, J. Belwin Edward, K. Sathish Kumar, Avagaddi Prasad

“…Parameter extraction of a solar photovoltaic system is a nonlinear problem. Many optimization algorithms are implemented for this purpose, which failed in giving better results at low irradiance levels. …”
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Efficient decision procedure for Belief modality by Adomas Birštunas

“…Applied loop-check technique is not optimized and therefore loop-check takes most of the time used in decision algorithm. …”
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Cloud Model Bat Algorithm by Yongquan Zhou, Jian Xie, Liangliang Li, Mingzhi Ma

“…Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. …”
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Enhanced Production of Cellulase from Pineapple Waste by Response Surface Methodology by P. Saravanan, R. Muthuvelayudham, T. Viruthagiri

“…Optimization of the media components for cellulase production using Trichoderma reesei was carried out. …”
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Applications of Matrices to a Matroidal Structure of Rough Sets by Jingqian Wang, William Zhu

“…They are widely used in attribute reduction in data mining. There are many optimization issues in attribute reduction. Matroids generalize the linear independence in vector spaces and are widely used in optimization. …”
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Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based Learning by Chao Yang, Jian-Ke Zhang, Li-Xin Guo

“…The artificial bee colony (ABC) algorithm is a recently introduced optimization method in the research field of swarm intelligence. …”
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Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management by Zhuojie Li

“…According to the BP neural network algorithm, for the problem that the input variables of the BP network cannot be automatically optimized during the modeling process of the multivariable complex system, it is used to establish a neural network optimization algorithm according to the gray correlation analysis (GM2 BPANN). …”
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Modeling and Performance Analysis of Energy Efficiency Binary Power Control in MIMO-OFDM Wireless Communication Systems by Yuming Wang, Xiaohu Ge, Chengqian Cao, Xi Huang, Frank Y. Li

“…The energy efficiency optimization of the binary power control scheme for MIMO-OFDM wireless communication systems is formulated, and then a global optimization solution of power allocation is derived. …”
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A Heuristic Algorithm for Solving Triangle Packing Problem by Ruimin Wang, Yuqiang Luo, Jianqiang Dong, Shuai Liu, Xiaozhuo Qi

“…For example, the polygon is not allowed to rotate; then, the approximate solution can be obtained by optimization method. This paper studies the triangle packing problem by a new kind of method. …”
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Prediction and Analysis of Slope Stability Based on IPSO-SVM Machine Learning Model by Yu Wang, Erxia Du, Sanqiang Yang, Li Yu

“…Considering the above characteristics, this study proposes an improved particle swarm optimization of support vector machine (IPSO-SVM) algorithm model, which combines optimized particle swarm optimization (IPSO) and support vector machine (SVM) and applies it to slope stability prediction. …”
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