Robust DWT-HMM image watermarking algorithm optimized with content-adaptive approach by WANG Chun-tao1, NI Jiang-qun1, HUANG Ji-wu1, ZHANG Rong-yue1, LUO Xi-zhang1

“…A robust watermarking algorithm based on content-adaptive approach was proposed to optimize the tradeoff between robustness and imperceptibility,which was characterized as follows: the entropy masking proposed by Watson etc.was constructed in wavelet domain,which was then used to constitute the integrated HVS model;three different measures,namely,energy,entropy and integrated HVS,for content-adaptive selection were constructed and investigated;repeat-accumulate（RA） code with erasure and error correction was used to tackle the synchronization issue of the exact positions for watermark embedding;and a posteriori DWT-HMM detector was utilized for watermark detection.Simula-tion results show that the proposed content-adaptive watermarking algorithm,under the same imperceptibility,has con-siderable improvement in robustness performance over the traditional one with stochastic approach.…”
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Multi-Condition Magnetic Core Loss Prediction and Magnetic Component Performance Optimization Based on Improved Deep Forest by Haotian Shi, Zipeng Jin

“…To achieve high efficiency and high power density designs, it is essential to study core loss characteristics and optimize operating parameters. This paper proposes a core loss prediction model based on an improved deep forest algorithm and information entropy-enhanced genetic algorithm. …”
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Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…[Objective] Factors such as road networks， temperature， and electric vehicle （EV） type affect the spatial and temporal distribution of EV charging loads. To improve prediction accuracy， a spatiotemporal EV charging load prediction model is developed by integrating multiparty information. …”
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Improving Forecasts of the EGARCH Model Using Artificial Neural Network and Fuzzy Inference System by Geleta T. Mohammed, Jane A. Aduda, Ananda O. Kube

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Improvement of Assemble-to-Order Model Processes With Process Mining: Dynamic Analysis and Hybrid Approaches by Ufuk Celik, Yuksel Yurtay

“…Insights derived from the analysis informed actionable recommendations to optimize production workflows. This study demonstrates the potential of hybrid process mining techniques for understanding and improving ATO systems, offering a dynamic and scalable framework for addressing inefficiencies in similar production models.…”
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Risk assessment and hybrid algorithm transportation path optimization model for road transport of dangerous goods by Qiankun Jiang, Haiyan Wang

“…After experimental verification, the improved hybrid algorithm has optimized the path transportation time by 13.9 % compared to a single algorithm model. …”
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Optimized Grasshopper Optimisation Algorithm enabled DETR (DEtection TRansformer) model for skin disease classification. by Shakti Kundu, Yogesh Kumar Sharma, Khan Vajid Nabilal, Gopalsamy Venkatesan Samkumar, Sultan Mesfer Aldossary, Shanu Kuttan Rakesh, Nasratullah Nuristani, Arshad Hashmi

“…Hyperparameter tuning using GOA optimizes the critical parameters of the proposed model to improve classification accuracy. …”
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Coordinated System Intelligent Optimization for an Ultra-Supercritical Power Unit Based on Improved Simplex Method and Condensate Throttling by Liangyu MA, Qianqian LI, Fan LI

“…Based on the established models, a classic optimization theory-improved simplex method was selected as the CCS optimization algorithm. …”
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Optimization of a photovoltaic/wind/battery energy-based microgrid in distribution network using machine learning and fuzzy multi-objective improved Kepler optimizer algorithms by Fude Duan, Mahdiyeh Eslami, Mohammad Khajehzadeh, Ali Basem, Dheyaa J. Jasim, Sivaprakasam Palani

“…The variables are microgrid optimal location and capacity of the HMG components in the network which are determined through a multi-objective improved Kepler optimization algorithm (MOIKOA) modeled by Kepler’s laws of planetary motion, piecewise linear chaotic map and using the FDMT. …”
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GRL-ITransformer: An Intelligent Method for Multi-Wind-Turbine Wake Analysis Based on Graph Representation Learning With Improved Transformer by Kang Han, Li Xu

“…In our study, we propose a graph representation learning model with improved Transformer (GRL-ITransformer) to better integrate feature information, so that the model can capture the dynamic time relationship of different variables and establish its spatial relationship, striving to enhance the precision in predicting wind turbine wake field. …”
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Improving Cardiovascular Disease Prediction through Stratified Machine Learning Models and Combined Datasets by Tara Yousif Mawlood, Alla Ahmad Hassan, Rebwar Khalid Muhammed, Aso M. Aladdin, Tarik A. Rashid, Bryar A. Hassan

“…Results revealed that ensemble models, particularly RF and DT, achieved optimal performance with 100% accuracy, while stratification significantly improved the outcomes of SVM, GNB, and GB. …”
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Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements by Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen

“…This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. …”
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Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nong... by Yuxiang Wang, Zhangwei Chen, Hongfei Zu, Xiang Zhang, Chentao Mao, Zhirong Wang

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Models and Algorithms of Conflict Detection and Scheduling Optimization for High-Speed Train Operations Based on MPC by Zhihui Wang, Yonghua Zhou, Deng Liu

“…Compared with the general-speed railway transportation, the high-speed railway transportation requires a timely and automatic adjustment capability in the centralized traffic control (CTC) system. In order to improve the capability, this paper mainly explores the models and algorithms of conflict detection and scheduling optimization of high-speed train operations. …”
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Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples by Abdullahi G. Usman, Sagiru Mati, Hanita Daud, Ahmad Abubakar Suleiman, Sani I. Abba, Hijaz Ahmad, Taha Radwan

“…This study proposed the use of a support vector regression (SVR) predictive model improved by two metaheuristic algorithms used for optimization namely, Harris Hawks Optimization (HHO) and Particle Swarm Optimization (PSO) to predict chromatographic retention time of various food mycotoxin groups. …”
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Enhancing Surgery Scheduling in Health Care Settings With Metaheuristic Optimization Models: Algorithm Validation Study by João Lopes, Tiago Guimarães, Júlio Duarte, Manuel Santos

“…By implementing these AI-driven strategies, hospitals can minimize patient wait times, maximize resource use, and enhance surgical outcomes through improved planning. This development highlights how AI algorithms can effectively adapt to changing health care environments, having a transformative impact.…”
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Automated weed and crop recognition and classification model using deep transfer learning with optimization algorithm by K. Gopalakrishnan, R. Sivaraj, M. Vijayakumar

“…The extensive outcome highlighted the improvements of the developed AWRC-DLMLO technique with other existing models.…”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

“…This study investigates the impact of multiple optimization algorithms within transfer learning, employing EfficientNet models for the classification of agricultural insects. …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

“…This study investigates the impact of multiple optimization algorithms within transfer learning, employing EfficientNet models for the classification of agricultural insects. …”
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Anomaly Detection and Performance Analysis With Exponential Smoothing Model Powered by Genetic Algorithms and Meta Optimization by Ali Kerem Guler, Huseyin Fuat Alsan, Taner Arsan

“…This study employs a genetic algorithm to optimize the parameters of the Third Order Exponential Smoothing model for predicting on the real-time traffic datasets of the Numenta Anomaly Benchmark (NAB). …”
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