AI-Based Classification Model for Low-Energy Buildings: Promoting Sustainable Economic Development of Smart Cities With Spherical Fuzzy Decision Algorithm by Lin Yang

“…These models classify buildings based on energy consumption patterns, predicting energy needs and identifying areas for improvement. …”
Get full text

Dynamical Modeling, Analysis, and Control of Information Diffusion over Social Networks: A Deep Learning-Based Recommendation Algorithm in Social Network by Kefei Cheng, Xiaoyong Guo, Xiaotong Cui, Fengchi Shan

Get full text

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. …”
Get full text

An improved extreme learning machine algorithm for prospectivity mapping of copper deposits using multi-source remote sensing data: a case study in the North Altyn Tagh, Xinjiang,... by Boqi Yuan, Qinjun Wang, Wentao Xu, Chaokang He, Wenyue Xie

Get full text

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). …”
Get full text

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. …”
Get full text

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. …”
Get full text

Optimization of a Time-of-Arrival-Ridge Estimation Iterative Model for Ultra-Wideband Positioning in a Long Linear Area by Mengqian Li, Mingduo Li, Jinhua Wang, Aoze Duan, Haotian Sun, Qinggang Meng

Get full text

A Method for Quantifying Mung Bean Field Planting Layouts Using UAV Images and an Improved YOLOv8-obb Model by Kun Yang, Xiaohua Sun, Ruofan Li, Zhenxue He, Xinxin Wang, Chao Wang, Bin Wang, Fushun Wang, Hongquan Liu

“…The results indicated that on the 13th day post seeding, a 2640 × 1978 image captured at 7 m above ground level exhibited optimal detection performance. Compared with YOLOv8, YOLOv8-obb, YOLOv9, and YOLOv10, the YOLOv8-obb-p2 model improved precision by 1.6%, 0.1%, 0.3%, and 2%, respectively, and F1 scores improved by 2.8%, 0.5%, 0.5%, and 3%, respectively. …”
Get full text

Improved Set-point Tracking Control of an Unmanned Aerodynamic MIMO System Using Hybrid Neural Networks by Oduetse Matsebe, David Mohammed Ezekiel, Ravi Samikannu

Get full text

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. …”
Get full text

Machine learning via DARTS-Optimized MobileViT models for pancreatic Cancer diagnosis with graph-based deep learning by Yusuf Alaca

Get full text

An Enhanced IDBO-CNN-BiLSTM Model for Sentiment Analysis of Natural Disaster Tweets by Guangyu Mu, Jiaxue Li, Xiurong Li, Chuanzhi Chen, Xiaoqing Ju, Jiaxiu Dai

“…The improved DBO (IDBO) algorithm is then utilized to optimize the Convolutional Neural Network—Bidirectional Long Short-Term Memory (CNN-BiLSTM) model’s hyperparameters. …”
Get full text

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. …”
Get full text

Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy by T. Yuvaraj, T. Sengolrajan, Natarajan Prabaharan, K. R. Devabalaji, Akie Uehara, Tomonobu Senjyu

“…To demonstrate the effectiveness of the proposed approach, IGWO-PSO is compared with other hybrid optimization algorithms. Validation on a modified IEEE 33-bus RDN confirms that the proposed model enhances VPP placement and sizing, leading to improved economic, operational, and resilience metrics. …”
Get full text

Hybrid Darknet53-SVM model with random grid search optimization for enhanced colorectal cancer histological image classification by Pragati Patharia, Prabira Kumar Sethy, K. Lakshmipathi Raju, Anita Khanna, Ashoka Kumar Ratha, Santi Kumari Behera, Aziz Nanthaamornphong

“…To enhance the classification performance, Darknet53 was hybridized with a SVM by replacing the dense layer, and hyperparameters were optimized using a Random Grid Search algorithm. The optimized hybrid model exhibited a remarkable improvement, with an Acc. of 99.7%, Sen. of 99.7%, Spec. of 99.91%, Prec. of 99.98%, and F1-score of 99.98%, alongside significant improvements in other metrics. …”
Get full text

Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

“…Furthermore, metaheuristic algorithms like Smell Agent Optimization and Giant Trevally Optimizer were employed to optimize model's hyperparameters, with the intention of enhancing accuracy and precision in performance estimations. …”
Get full text

Recurrent academic path recommendation model for engineering students using MBTI indicators and optimization enabled recurrent neural network by Anupama V, Sudheep Elayidom M

“…To address this issue, an intelligent recommendation model is proposed that assists students in discovering the most suitable academic path based on their personal background and personality traits. …”
Get full text

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. …”
Get full text

Applicability of elite samples in solving the traveling salesman problem by Goldberg model by Valery G. Kobak, Irma S. Rudova

Get full text