Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…Hybrid models combine the strengths of different algorithms, achieving 80–90% accuracy on average, and are particularly effective in complex, multi-faceted projects. …”
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Power quality enhancement based disturbance rejection controller in microgrid system using walrus optimization algorithm and multi-functional recurrent fuzzy neural network by Ali M.H. Al Thaiban, Akram Elmitwally, Abdelhady Ghanem, Ahmed I. Omar

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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…Accurate and reliable crop yield prediction is essential for optimizing agricultural management, resource allocation, and decision-making, while also supporting farmers and stakeholders in adapting to climate change and increasing global demand. …”
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Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study by Chanmin Park, Changho Han, Su Kyeong Jang, Hyungjun Kim, Sora Kim, Byung Hee Kang, Kyoungwon Jung, Dukyong Yoon

“…External validation was performed using data from 670 patients at Ajou University Hospital (March 2022 to September 2022). We evaluated machine learning algorithms (random forest [RF], extra-trees classifier, and light gradient boosting machine) and selected the RF model as the final model based on its performance. …”
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A hybrid path planning algorithm combining A* and improved ant colony optimization with dynamic window approach for enhancing energy efficiency in warehouse environments by Mingyu Wu, Eileen Lee Ming Su, Che Fai Yeong, Bowen Dong, William Holderbaum, Chenguang Yang

“…Future work will focus on further optimizing the algorithm and integrating machine learning techniques for enhanced adaptability and performance.…”
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Research on Longitudinal Intelligent Control of Autonomous-rail Rapid Tram by TANG Liang, SHEN Mengyu, XIAO Lei

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A Closest Resemblance Classifier with Feature Interval Learning and Outranking Measures for Improved Performance by Nabil Belacel

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Pixel and region-oriented classification of Sentinel-2 imagery to assess LULC dynamics and their climate impact in Nowshera, Pakistan by Farnaz, Nuthammachot Narissara, Shabbir Rabia, Iqbal Benazeer

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Advanced Computational Methods for Mitigating Shock and Vibration Hazards in Deep Mines Gas Outburst Prediction Using SVM Optimized by Grey Relational Analysis and APSO Algorithm by Xiang Wu, Zhen Yang, Dongdong Wu

“…Despite these progresses, predicting the gas outburst more accurately and efficiently still remains a great challenge. In this work, an algorithm based on grey relational analysis and SVM using adaptive particle swarm optimization (APSO-SVM) for gas outburst prediction is proposed. …”
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Scalable earthquake magnitude prediction using spatio-temporal data and model versioning by Rahul Singh, Bholanath Roy

“…Multiple machine learning algorithms, including Gradient Boosting, Light Gradient Boosting Machine (LightGBM), XGBoost, and Random Forest, are evaluated on dataset sizes of 20%, 35%, 65%, and 100%, with performance metrics such as Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, and R 2. …”
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Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port by Hamza Garmouch, Otman Abdoun

“…GA-based optimization allows for adaptive learning, parameterization, and real-time adaptation, significantly improving OCR accuracy, reducing error rates, and optimizing system uptime. …”
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Area-based face curve characteristic analysis to recognize Multimodal 2D/3D monozygotic twins using Simpson’s rule and Machine Learning by Gangothri Sanil, Krishna Prakasha, Srikanth Prabhu, Vinod C. Nayak

“…To more accurately identify and analyze the facial differences and compare the twin faces, the resulting area-based score is then used as input to various machine learning algorithms such as Extreme gradient boosting (XGBoost), Adaptive Boosting (AdaBoost) classifiers, Random Forest (RF) classifiers, Light Gradient Boosting Model(LGBM), and Extra Tree Classifier(ETC) classifiers, etc. …”
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Advancing named entity recognition in interprofessional collaboration and education by Rui Zhang, Yifeng Shan, MengZhe Zhen

“…ASOS complements this by employing real-time feedback loops, conflict resolution algorithms, and resource reallocation strategies to iteratively refine contributions and interactions.ResultsExperimental evaluations demonstrate significant improvements in entity recognition accuracy, conflict mitigation, and overall collaboration efficiency compared to baseline methods.DiscussionThis study advances the theoretical and practical applications of NER in IPC, ensuring scalability and adaptability to complex, real-world scenarios.…”
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Combined influence of crushed brick powder and recycled concrete aggregate on the mechanical, durability and microstructural properties of eco-concrete: An experimental and machine... by Md. Habibur Rahman Sobuz, Mahmudur Hossain Khan, Md. Rakibul Islam, Md. Kawsarul Islam Kabbo, Abdullah Alzlfawi, M Jameel, Md. Munir Hayet Khan

“…Additionally, the study evaluates machine learning algorithms such as extreme gradient boosting (XG Boost), random forest (RF), and bagging model (BAG) for predicting the mechanical strength of concrete specimens. …”
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The human-on-the-loop evaluation of multiobjective optimization algorithms for solving a real-world problem that integrates the food-energy-water nexus security and climate change... by Isaac Okola, Daniel Orwa Ochieng, Evans Kirimi Miriti, Gilbert Ouma Ong'isa

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Pedotransfer functions for estimating the van Genuchten model parameters in the Cerrado biome by Mariana F. Veloso, Lineu N. Rodrigues, Elpídio I. Fernandes Filho, Carolina F. Veloso, Bruna N. Rezende

“…Multiple Linear Regression (MLR) and four machine learning (ML) algorithms were used to develop the PTFs. …”
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Forestry climate adaptation with HarvesterSeasons service—a gradient boosting model to forecast soil water index SWI from a comprehensive set of predictors in Destination Earth by Mikko Strahlendorff, Anni Kröger, Golda Prakasam, Miriam Kosmale, Mikko Moisander, Heikki Ovaskainen, Asko Poikela

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Failure Detection of Laser Welding Seam for Electric Automotive Brake Joints Based on Image Feature Extraction by Diqing Fan, Chenjiang Yu, Ling Sha, Haifeng Zhang, Xintian Liu

“…Compared with infrared and ultrasonic detection methods, the proposed machine-vision-based detection system has significant advantages in detection speed, surface defect recognition accuracy, and industrial adaptability. …”
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Safe and Robust Binary Classification and Fault Detection Using Reinforcement Learning by Josh Netter, Kyriakos G. Vamvoudakis, Timothy F. Walsh, Jaideep Ray

“…In this paper, we propose a learning-based method utilizing the Soft Actor-Critic (SAC) algorithm to train a binary Support Vector Machine (SVM) classifier. …”
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Developing an SSVEP-Based BCI System for Multi-Objective Control via IoT Integration by Jinsha Liu, Boning Li, Takaharu Yamazaki, Jianting Cao

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