Motion Shape Control of Superstructure in Base-Isolated Tall Buildings using GBMO-Based Uniform Deformation Techniques by Sadegh Etedali

“…For these purposes, an optimization procedure based on a gas Brownian motion optimization (GBMO) algorithm is defined. …”
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Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

“…This work points out the possibility of taking complete advantage of advanced machine learning algorithms along with metaheuristics optimization in improving photocatalytic processes, hence opening a bright avenue for real applications in water treatment.…”
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Optimizing spatial normalization of multisubject inner ear MRI: comparison of different geometry-preserving co-registration approaches by Johannes Gerb, Valerie Kirsch, Emilie Kierig, Thomas Brandt, Marianne Dieterich, Rainer Boegle

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Waveform design and signal processing for terahertz integrated sensing and communication by Xianbin YU, Zhidong LYU, Lianyi LI, Muhammad Idrees Nazar, Lu ZHANG

“…Integrated sensing and communication (ISaC) in the terahertz band can efficiently reduce the consumption of hardware and spectrum resources, while improving the transmission data rate and sensing resolution.Firstly, the development status of ISaC, terahertz communication and sensing were briefly introduced.Then, the strategy of waveform design and optimization for ISaC and the receiving signal processing algorithms were presented.As an example, an OFDM ISaC system operating at 97 GHz was experientially demonstrate, and the performance of ranging, speed and communication were all evaluated in the experiment.Finally, the key issues and research directions of future terahertz ISaC development were discussed.…”
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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

“…Grid search optimization was employed to fine-tune the hyperparameters of each model, while model evaluation was conducted using 10-fold cross-validation and six performance metrics. …”
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Path planning of unmanned ships based on A* and dynamic window approach by FU Long, SHEN Zhen, TAO Hao, HAN Yunjun, DONG Xisong, XIONG Gang

“…The A* algorithm computed the global shortest path in a static environment, while the improved DWA optimized local path obstacle avoidance between path nodes. …”
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Remaining useful life prediction of a small sample of aero-engine based on an improved gray Markov model by Dong-hai Li, Ji-liang Tu, Hui Liu, Nai-zhi Liao

“…To enhance adaptability, a genetic algorithm dynamically optimizes the time response parameters of the grey model, overcoming the limitation of a fixed structure in traditional methods. …”
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Generative design recommendations for the historical Mardiṅ High School and Gaziṗaşa Primary School buildings, Turkey by Mizgin Gökçe Salık, Fatma Demet Aykal

“…The genetic algorithm (GA) is inspired by natural selection, emphasizing the survival of the fittest. …”
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Brain age prediction from MRI images based on a convolutional neural network with MRMR feature selection layer by Mustafa Hatem Al Ghariri, Seyed Omid Shahdi

“…The feature selection layer uses MRMR algorithm which identifies essential characteristics for a target variable while minimizing feature redundancy to select the optimal feature subset. …”
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Neural network inspired efficient scalable task scheduling for cloud infrastructure by Punit Gupta, Arnaav Anand, Pratyush Agarwal, Gavin McArdle

“…In this work, we aim to use the Harmony Search Algorithm and neural networks to create a fault aware system for optimal usage of cloud resources. …”
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Hybrid Machine Learning Model for Predicting Shear Strength of Rock Joints by Daxing Lei, Yaoping Zhang, Zhigang Lu, Hang Lin, Yifan Chen

“…To address these challenges, this study proposes a hybrid ML model that integrates a multilayer perceptron (MLP) with the slime mold algorithm (SMA), termed the SMA-MLP model. While MLP exhibits strong nonlinear mapping capability, SMA enhances its training process through global optimization and parameter tuning, thereby improving predictive accuracy and robustness. …”
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Convolutional neural networks for accurate estimation of canopy cover by F. Puig, R. Gonzalez Perea, A. Daccache, M.A. Soriano, J.A. Rodríguez Díaz

“…Deploying an RGB camera across various crops (wheat, alfalfa, and sweet pepper) in Spain and California, we harnessed a dataset comprising 283,000 images, each with dimensions of 256 × 256 pixels, for network training. Optimizing the neural network was achieved through a Genetic Algorithm (GA), employing an objective function focused on minimizing parameter density while maintaining accuracy. …”
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Runtime–Coherence Tradeoffs for Hybrid Satisfiability Solvers by Vahideh Eshaghian, Soren Wilkening, Johan Aberg, David Gross

“…Finally, we present numerical simulations, which suggest additional flexibility in implementing hybrid algorithms with the optimal tradeoff.…”
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‌Rockburst intensity grading prediction based on the LOF-ENN-KNN model‌ by Haoran Ge, Jiyong Zhang, Congbo Ma, Kai Hui, Yicong Li, Ziniu Wu

“…Through the comparison and exploration of different sampling methods and different combinations of LOF algorithm, single resampling technology (SMOTE, ADASYN) or simple technology superposition (LOF-SMOTE, LOF-ADASYN) is easy to introduce over-fitting or negative coupling effect, while LOF-ENN-KNN significantly improves the robustness and generalization ability of the model through modular design. …”
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E-Commerce Logistics Software Package Tracking and Route Planning and Optimization System of Embedded Technology Based on the Intelligent Era by Dan Zhang, Zhiyang Jia

“…From the experimental results, in terms of average delivery time, the algorithm’s result was 25.95 hr, while the traditional algorithm was 32.53 hr; in terms of average distribution freight cost, the algorithm’s result was 163.3 yuan, while the traditional algorithm was 257.7 yuan; in terms of average distribution cost, this algorithm’s result was 131.53 yuan, while the traditional algorithm was 211.68 yuan. …”
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RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

“…The graphs are processed using a graph neural network with DiffPool. To optimize feature integration, we incorporate an improved dung beetle optimization algorithm, which adaptively assigns fusion weights during inference. …”
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Prediction of carbon dioxide emissions from Atlantic Canadian potato fields using advanced hybridized machine learning algorithms – Nexus of field data and modelling by Muhammad Hassan, Khabat Khosravi, Aitazaz A. Farooque, Travis J. Esau, Alaba Boluwade, Rehan Sadiq

“…In this study, three novel machine learning algorithms of additive regression-random forest (AR-RF), Iterative Classifier Optimizer (ICO-AR-RF), and multi-scheme (MS-RF) were explored for carbon dioxide (CO2) flux rate prediction from three agricultural fields. …”
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Maximizing the Total Profit of Combined Systems with a Pumped Storage Hydropower Plant and Renewable Energy Sources Using a Modified Slime Mould Algorithm by Le Chi Kien, Ly Huu Pham, Minh Phuc Duong, Tan Minh Phan

“…A modified slime mould algorithm (MSMA) is applied to System 2 after proving its outstanding performance compared to the jellyfish search algorithm (JS), equilibrium optimizer (EO), and slime mould algorithm (SMA) in System 1.…”
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Smart home power management algorithm using real-time model predictive control for a stand-alone PV system with battery energy storage by Aziz Watil

“…The overall battery efficiency reached 96.45%, demonstrating the algorithm’s ability to optimize power flow, ensure a reliable energy supply, and maintain battery safety under varying weather conditions.…”
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Direction of Arrival (DOA) Estimation Using a Deep Unfolded Learned Iterative Shrinkage Thresholding Algorithm (LISTA) Network in a Non-Uniform Metasurface by Xinyi Niu, Xiaolong Su, Lida He, Guanchao Chen

“…To address these issues, we optimize a non-uniform metasurface array to reduce hardware costs and mutual coupling effects while enhancing resolution. …”
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