Machine Learning Model for Hepatitis C Diagnosis Customized to Each Patient by Leran Chen, Ping Ji, Yongsheng Ma

“…A general-purpose machine learning algorithm depends on a large amount of data and requires abundant computing power support, relies on the average level to describe the model performance, and cannot achieve optimal results on a specific problem. …”
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Model-Data Hybrid-Driven Real-Time Optimal Power Flow: A Physics-Informed Reinforcement Learning Approach by Ximing Zhang, Xiyuan Ma, Yun Yu, Duotong Yang, Zhida Lin, Changcheng Zhou, Huan Xu, Zhuohuan Li

“…Specifically, the proposed methodology uses the proximal policy optimization (PPO) algorithm as the agent’s foundational framework and constructs a PI-actor network embedded with prior model knowledge derived from power flow sensitivity into the agent’s actor network via the PINN method, which achieves dual optimization objectives: (a) enhanced environmental perceptibility to improve experience utilization efficiency via gradient-awareness from model knowledge during actor network updates, and (b) improved user trustworthiness through mathematically constrained action gradient information derived from explicit model knowledge, ensuring actor updates adhere to safety boundaries. …”
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Enhanced brain tumor diagnosis using combined deep learning models and weight selection technique by Karim Gasmi, Najib Ben Aoun, Najib Ben Aoun, Khalaf Alsalem, Ibtihel Ben Ltaifa, Ibrahim Alrashdi, Lassaad Ben Ammar, Manel Mrabet, Abdulaziz Shehab

“…This study underscores the potential of combining advanced deep learning models with a genetic algorithm-optimized weighting strategy to tackle complex medical classification tasks. …”
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Transformer based models with hierarchical graph representations for enhanced climate forecasting by T. Bhargava Ramu, Raviteja Kocherla, G. N. V. G. Sirisha, V. Lakshmi Chetana, P. Vidya Sagar, R. Balamurali, Nanditha Boddu

“…To improve computational efficiency and feature selection, we introduce a hybrid optimization approach (HWOA-TTA) that combines the Whale Optimization Algorithm (WOA) and Tiki-Taka Algorithm (TTA). …”
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Economic approach for optimal allocation of irrigation water in water-scarce region by Xueliang Zhang, Li Ren, Jianshi Zhao

“…This study proposes an economic approach to spatial irrigation allocation, based on the marginal benefit criterion, to improve both the explainability and efficiency of the optimization process. …”
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Low-Power Portable System for Power Grid Foreign Object Detection Based on the Lightweight Model of Improved YOLOv7 by Yonghuan He, Rong Wu, Chao Dang

“…Foreign objects caught and entangled on power grid transmission lines, power towers and other equipment can pose potential threats to the power system. The detection algorithm for foreign objects in the power grid cannot achieve the optimal balance in terms of accuracy and efficiency. …”
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Machine-learning based optimizing the neutronic and thermal-hydraulic performance in a VVER-1000 mixed-core as well as fuel burnup assessment by A. Koraniany, G.R. Ansarifar

“…By integrating this neural network with a genetic algorithm, optimization was carried out to identify the optimal fuel placement and enrichment for loading the UTVS fuel assembly into the targeted reactor core. …”
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Mechanism- and data-driven algorithms of electrical energy consumption accounting and prediction for medium and heavy plate rolling by Qiang Guo, Zimeng Zhou, Jie Li, Fengwei Jing

“…Energy consumption accounting and prediction in the medium and thick plate rolling process are crucial for controlling costs, improving production efficiency, optimizing equipment management, and enhancing the market competitiveness of enterprises. …”
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Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale by Harsh Vazirani, Xiaofeng Wu, Anurag Srivastava, Debajyoti Dhar, Divyansh Pathak

“…Specifically, this study aims to (1) create an integrated dataset combining remote sensing and ground data for comprehensive SOC analysis, (2) develop a new optimization technique that enhances both machine learning and deep learning model performance, and (3) evaluate the algorithm’s efficiency and accuracy against established optimization methods like Jaya and GridSearchCV. …”
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Study on the Impact of Input Parameters on Seawater Dissolved Oxygen Prediction Models by Wenqing Li, Jing Lv, Yuhang Wang, Xiangfeng Kong

“…Future research will develop a parameter adaptive selection algorithm, conduct the dynamic monitoring of multi-scale environmental factors, and achieve the intelligent optimization and verification of model parameters.…”
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A Framework for Flood Disaster Detection From Remote Sensing Images Using Spatiotemporal Fusion With Digital Twin Technology by Se-Jung Lim, K. Sakthidasan Sankaran, Anandakumar Haldorai

“…A feature extraction process is carried with the use of Deep Convolution VGGNet-16 from which optimal features are selected using Improved Harris Hawks Optimization algorithm (IHHOA). …”
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RON‐based cross‐chain routing optimization strategy in metaverse by Junjie Huang, Liang Tan, Jianmei Xiao

“…The current cross‐chain communication mode is dominated by direct‐connect routing, leading to network congestion and high propagation delay once the direct‐connect link fails and cannot be recovered quickly. To optimize direct‐connect routing, this paper proposed a cross‐chain routing optimization strategy based on RON (Resilient Overlay Network), that is, Cross‐Chain_RON, which firstly applies RON to reconstruct the direct‐connect routing model, and then selects the optimal link through the shortest‐path algorithm and policy routing, and combines with the RON performance database to improve the data transmission efficiency. …”
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Numerical Study on Energy-saving Optimal Control of Rotary Desiccant Wheel System by Zhang Nan, Yao ye, Jia Dongxin

“…A weight factor was introduced to combine the energy consumption and dehumidification performance of the system as the optimization objective. An energy-saving optimization control model of the desiccant wheel system was proposed with an improved PSO as the solution algorithm. …”
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Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

“…Based on those, an on-line soft sensor model of hot metal[Si] with the optimal parameters was obtained by using the multi-objective genetic algorithm (NSGA-Ⅱ) with the non-dominated sort and elitist strategy. …”
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Influence of soil parameters on dynamic compaction: numerical analysis and predictive modeling using GA-optimized BP neural networks by Yu Zhang, Xueshui Chen, Huakang Ge, Zhigang Guo, Xu Li

“…Orthogonal experimental design and single factor analysis were used to quantify the influence of each parameter on the compaction volume. In order to improve the prediction accuracy, this paper introduces genetic algorithm (GA) to optimize the BP neural network model, constructs a multi-factor dynamic compaction prediction model, and compares it with the traditional BP model. …”
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A Classification-Based Blood–Brain Barrier Model: A Comparative Approach by Ralph Saber, Sandy Rihana

“…<b>Methods</b>: In this study, we compare the effectiveness of sequential feature selection (SFS) and genetic algorithms (GAs) in optimizing descriptor selection for BBB permeability prediction. …”
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Recurrent academic path recommendation model for engineering students using MBTI indicators and optimization enabled recurrent neural network by Anupama V, Sudheep Elayidom M

“…At last, an adaptive recommendation of the engineering department is performed using DRNN, which is trained based on the Magnetic Invasive Weed Optimization (MIWO) algorithm. On the other hand, MBTI personality type categorization is done, wherein the correlation of courses with MBTI outcome is detected using MIWO-based DRNN. …”
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Optimization Strategy of a Stacked Autoencoder and Deep Belief Network in a Hyperspectral Remote-Sensing Image Classification Model by Xiaoai Dai, Junying Cheng, Shouheng Guo, Chengchen Wang, Ge Qu, Wenxin Liu, Weile Li, Heng Lu, Youlin Wang, Binyang Zeng, Yunjie Peng, Shuneng Liang

“…Two feature extraction algorithms, the autoencoder (AE) and restricted Boltzmann machine (RBM), were used to optimize the classification model parameters. …”
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Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials by Simin Nazari, Amira Abdelrasoul

“…The application of machine learning in predicting affinity energy holds significant promise for researchers and professionals in hemodialysis. These models, by enabling early interventions in hemodialysis membranes, could enhance patient safety and optimize the care of hemodialysis patients.…”
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Coverage path planning for multi-AUV considering ocean currents and sonar performance by Xukai Mu, Wei Gao

“…To address the CPP of multiple AUVs (multi-AUV) considering both sonar performance and ocean currents, we propose a new integrated algorithm based on the improved Dijkstra algorithm, Particle Swarm Optimization (PSO), and the ELKAI Solve. …”
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