LimeSoDa: A dataset collection for benchmarking of machine learning regressors in digital soil mapping by Jonas Schmidinger, Sebastian Vogel, Viacheslav Barkov, Anh-Duy Pham, Robin Gebbers, Hamed Tavakoli, Jose Correa, Tiago R. Tavares, Patrick Filippi, Edward J. Jones, Vojtech Lukas, Eric Boenecke, Joerg Ruehlmann, Ingmar Schroeter, Eckart Kramer, Stefan Paetzold, Masakazu Kodaira, Alexandre M.J.-C. Wadoux, Luca Bragazza, Konrad Metzger, Jingyi Huang, Domingos S.M. Valente, Jose L. Safanelli, Eduardo L. Bottega, Ricardo S.D. Dalmolin, Csilla Farkas, Alexander Steiger, Taciara Z. Horst, Leonardo Ramirez-Lopez, Thomas Scholten, Felix Stumpf, Pablo Rosso, Marcelo M. Costa, Rodrigo S. Zandonadi, Johanna Wetterlind, Martin Atzmueller

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Performance evaluation, optimization and dynamic decision in blockchain systems: a recent overview by Quan-Lin Li, Yan-Xia Chang, Qing Wang

“…This paper provides a recent systematic overview of this class of research, and especially, developing mathematical modeling and basic theory of blockchain systems. Important examples include (a) performance evaluation: Markov processes, queuing theory, Markov reward processes, random walks, fluid and diffusion approximations, and martingale theory; (b) performance optimization:Linear programming, nonlinear programming, integer programming, and multi-objective programming; (c) optimal control and dynamic decision: Markov decision processes, and stochastic optimal control; and (d) artificial intelligence: Machine learning, deep reinforcement learning, and federated learning. …”
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Optimized deep neural network architectures for energy consumption and PV production forecasting by Eghbal Hosseini, Barzan Saeedpour, Mohsen Banaei, Razgar Ebrahimy

“…These findings demonstrate the significant potential of GA-PSO as an effective tool to optimize DNN models in energy forecasting applications.…”
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An Effective QoS-Aware Hybrid Optimization Approach for Workflow Scheduling in Cloud Computing by Min Cui, Yipeng Wang

“…First, the workflow scheduling problem in cloud computing is modeled as a multi-objective optimization problem. …”
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A Pellet 3D Printer: Device Design and Process Parameters Optimization by Shiyi Liu, Peng Zhao, Senyang Wu, Chengqian Zhang, Jianzhong Fu, Zichen Chen

“…Using the fused deposition modelling (FDM) method, some products were printed with this machine. …”
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Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification by Shahad Alkamli, Hala Alshamlan

“…This complexity necessitates advanced optimization methods for effective gene selection. <b>Methods</b>: This study introduces and evaluates the Nuclear Reaction Optimization (NRO)—drawing inspiration from nuclear fission and fusion—for identifying informative gene subsets in six benchmark cancer microarray datasets. …”
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Data-Driven Technologies for Energy Optimization in Smart Buildings: A Scoping Review by Joy Dalmacio Billanes, Zheng Grace Ma, Bo Nørregaard Jørgensen

“…However, the existing literature often lacks a holistic examination of the technological advancements, adoption barriers, and business models necessary to realize these benefits. To address this gap, this scoping review synthesizes current research on these technologies, identifies factors influencing their adoption, and examines supporting business models. …”
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The impact of tractor drawbar height on performance and optimization using response surface methodology by Ali Yavuz Şeflek, Nuri Orhan, Mete Özkan

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Prediction and optimization of robot processing technology based on neural network and genetic algorithm by Fusen WU

“…This model can clearly reveal the role of various grinding process parameters in machining and reflect their importance in improving machining efficiency and material removal rate. …”
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Jointly Optimized Placement of Application VM and VNF in NFV Based Data Center by Dandan Qi, Ruijun Gu

“…This paper is the first to deal with the problem of the joint optimization problem of AppVM and VNF placement. Firstly, we model the problem of the joint optimization problem of AppVM and VNF placement as a binary integer linear programming model. …”
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Building accurate numerical models by Sharapov Dmitry

“…The integration of emerging technologies like machine learning, artificial intelligence, and quantum computing holds significant promise for advancing numerical modeling capabilities. …”
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A turbines-module adapted to the marine site for tidal farms layout optimization by Micol Pucci, Debora Bellafiore, Stefania Zanforlin, Antonio Frangioni

“… In this work we propose a new methodology for tidal farm layout optimization. For the optimization process we adopt a simple Mixed Integer Quadratic Programming (MIQP) algorithm, coupled with a wake model. …”
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Anchor-Based Explainable and Causal Artificial Intelligence for Enhancing Financial Predictions of Future Earnings by Siriporn Sawangarreerak, Putthiporn Thanathamathee, Pankaewta Lakkanawanit, Nor Shaipah Abdul Wahab

“…Accurate prediction of future earnings is crucial for stakeholders. However, existing machine learning models often operate as &#x201C;black boxes,&#x201D; offering high accuracy but minimal interpretability. …”
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Advancing our understanding of optoionic effects for the design of solar batteries: a theoretical perspective by Matteo Rinaldi, Matthias Kick, Karsten Reuter, Christian Carbogno

“…This does however require expertise in various areas, including advanced electronic-structure theory, machine learning, and multi-scale approaches. In this perspective, we shed light on the intricacies of modeling optoionic effects for solar battery materials. …”
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Multi-Objective Optimization of the Rotary Turning of Hardened Mold Steel for Energy Saving and Surface Roughness Improvements by Tat Khoa Doan, Trung Thanh Nguyen, An-Le Van

“…The Bayesian regularized feed-forward neural network was applied to develop the SCE and Ra models. The entropy method and vibration and communication particle swarm optimization (VCPSO) algorithm were employed to compute the weights and determine optimal factors. …”
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Research on process optimization and trajectory planning of EA4T axle robot grinding by Feng ZHANG, Zhongli FENG, Feng XU, Deming ZHANG, Xiangrui ZENG, Jianwei MA, Shilei ZHANG

“…The 3D model of the EA4T axle is imported into the virtual environment. …”
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Leveraging Radiomics and Genetic Algorithms to Improve Lung Infection Diagnosis in X-Ray Images Using Machine Learning by A. Beena Godbin, S. Graceline Jasmine

“…To optimize the performance of machine learning models, the paper incorporates genetic algorithms for hyperparameter optimization. …”
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Diversifying Multi-Head Attention in the Transformer Model by Nicholas Ampazis, Flora Sakketou

“…Experiments on diverse NLP tasks, including machine translation, text summarization, question answering and large language modeling, show that our proposed approach consistently improves the performance of baseline Transformer models.…”
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Noise robust classification of carbide tool wear in machining mild steel using texture extraction based transfer learning approach for predictive maintenance by Ravi Sekhar, Sharnil Pandya, Pritesh Shah, Hemant Ghayvat, Deepak Sharma, Matthias Renz, Deep Shah, Adeeth Jagdale, Devansh Hukmani, Santosh Saxena, Neeraj Kumar

“…Moreover, three optimizers (RMSPROP, ADAM, SGDM) were applied to each of the deep learning models to enhance classification accuracies. …”
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Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms by Yuki Hanawa, Tomohiro Harada, Yukiya Miura

“…To reduce this cost, SAEAs employ surrogate models—machine learning models that approximate expensive evaluation functions. …”
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