Computationally Enhanced UAV-Based Real-Time Pothole Detection Using YOLOv7-C3ECA-DSA Algorithm by Siti Fairuz Mat Radzi, Mohd Amiruddin Abd Rahman, Muhammad Khairul Adib Muhammad Yusof, Nurin Syazwina Mohd Haniff, Romi Fadillah Rahmat

“…This study introduces YOLOv7-C3ECA-DSA, an improved YOLOv7 architecture designed to address these limitations. …”
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Improving the Predictability of the Madden‐Julian Oscillation at Subseasonal Scales With Gaussian Process Models by Haoyuan Chen, Emil Constantinescu, Vishwas Rao, Cristiana Stan

“…Abstract The Madden–Julian Oscillation (MJO) is an influential climate phenomenon that plays a vital role in modulating global weather patterns. In spite of the improvement in MJO predictions made by machine learning algorithms, such as neural networks, most of them cannot provide the uncertainty levels in the MJO forecasts directly. …”
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AAD-YOLO: An Improved YOLOv8 Model for Complex Remote Sensing Scenarios by Yue Hong, Yi Shu, Shuo Guo

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Improving 3D Reconstruction Through RGB-D Sensor Noise Modeling by Fahira Afzal Maken, Sundaram Muthu, Chuong Nguyen, Changming Sun, Jinguang Tong, Shan Wang, Russell Tsuchida, David Howard, Simon Dunstall, Lars Petersson

“…We collect a high-resolution RGB-D dataset and apply our noise model to improve tracking and produce higher-resolution 3D models.…”
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Improving thyroid disorder diagnosis via innovative stacking ensemble learning model by Ayesha Hassan, Shabana Ramzan, Ali Raza, Muhammad Munwar Iqbal, Aseel Smerat, Norma Latif Fitriyani, Muhammad Syafrudin, Seung Won Lee

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DCLTV: An Improved Dual-Condition Diffusion Model for Laser-Visible Image Translation by Xiaoyu Zhang, Laixian Zhang, Huichao Guo, Haijing Zheng, Houpeng Sun, Yingchun Li, Rong Li, Chenglong Luan, Xiaoyun Tong

“…To achieve more accurate laser-visible image translation, we designed an improved diffusion model, called DCLTV, which limits the randomness of diffusion models by means of dual-condition control. …”
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The Two-Stage Alzheimer’s Disease Automatic Diagnosis Algorithm Based on ST-MBV3 Model by Guiping Li, Zhenhao Jin, Minghui Deng, Junjie Gong, Piaoyi Zheng

“…This study focuses on leveraging these advancements to enhance the accuracy of AD diagnosis through a novel two-stage algorithm. The proposed model combines an improved 3D DenseNet segmentation model with an enhanced ST-MBV3 classification model. …”
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A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm by Tianli Wang, Yi Zhang, Haiyan Liu, Fei Li, Dayong Guo, Ning Cao, Yubin Zhang

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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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Multiradar Collaborative Task Scheduling Algorithm Based on Graph Neural Networks with Model Knowledge Embedding by Haoqing LI, Dian YU, Changchun PAN, Wenxian YU, Dongying LI

“…Therefore, this paper proposes a Model Knowledge Embedded Graph Neural Network (MKEGNN) scheduling algorithm. …”
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Renewable energy forecasting using optimized quantum temporal model based on Ninja optimization algorithm by Mona Ahmed Yassen, El-Sayed M. El-kenawy, Mohamed Gamal Abdel-Fattah, Islam Ismael, Hossam El.Deen Salah Mostafa

“…Experimental implementation revealed that incorporating the Ninja Optimization Algorithm with the QTM model delivered the best R2 performance at 95.15% with an exceptional RMSE value of 0.00003, thus establishing its ability to optimize renewable energy forecasting accuracy.…”
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Log-Viterbi algorithm applied on second-order hidden Markov model for human activity recognition by Yang Sung-Hyun, Keshav Thapa, M Humayun Kabir, Lee Hee-Chan

“…Therefore, this approach maximizes the probability of activity recognition with improved accuracy and reduced time complexity. We compared our proposed algorithm among other famous probabilistic models such as Naïve Bayes, condition random field, hidden Markov model, and hidden semi-Markov model using three datasets in the smart home environment. …”
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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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An equivalent modeling method for integrated water-wind-solar systems based on sparrow search algorithm by Yuanhong Lu, Jie Zhang, Jingyue Zhang, Libin Huang, Haiping Guo, Binjiang Hu, Tianyu Guo

“…This study proposes a cluster-based equivalent modeling approach for hybrid wind-solar-hydro power plants using the Sparrow Search Algorithm. …”
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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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Hybridization of Machine Learning Algorithms and an Empirical Regression Model for Predicting Debris-Flow-Endangered Areas by Xiang Wang, Mi Tian, Qiang Qin, Jingwei Liang

“…Results show that compared with the three individual machine-learning models, hybridization of machine-learning algorithms and the empirical model results in R2, RMSE, and MAE improved by 70.5%, 32.9%, and 41.1%, respectively. …”
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Intelligent irrigation strategy model for farmland using dung beetle optimization-random forest algorithms by Wenwen Hu, Yong Liu, Jun An, Shipu Xu, Zhiwen Zhou, Mingming An, Xiaokun Guo, Xiang Ma, Wenfei Jiang, Yunsheng Wang

“…This study proposes an optimized machine learning prediction model using the Dung Beetle Optimization-Random Forest (DBO-RF) algorithm, thus improving irrigation predictability. …”
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Precision evaluation criteria for simulation algorithms in infinite systems: A network model-based approach by Yonglong Ding

“…As the particle count escalates, the computational demands of diverse simulation algorithms surge, paralleled by a marked improvement in accuracy. …”
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A multi-stage auditory model for binaural sound localization using the locally competitive algorithm by Evelyn E. Ware, Michael T. Roberts, Michael P. Flynn

“…The proposed model achieves a localization accuracy of 95%, comparable to human performance, through a novel application of the Locally Competitive Algorithm (LCA) for efficient sparse coding of auditory signals. …”
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