Distributed robust scheduling of distribution-microgrid based on deep learning method integration by WANG Yihong, LIU Jichun, QIU Gao, ZHOU Hao, HE Peixin

“…The two-stage rolling scheduling optimization model of multi-microgrid is established, namely, the first-stage pre-scheduling model and the second-stage real-time regulation model. …”
Get full text

Predictive analytics in customer behavior: Anticipating trends and preferences by Hamed GhorbanTanhaei, Payam Boozary, Sogand Sheykhan, Maryam Rabiee, Farzam Rahmani, Iman Hosseini

Get full text

A CPSO-BPNN-Based Analysis of Factors Influencing the Mental Health of Urban Youth by Hu Xiang, Yong-Hong Lan

“…The results are obtained by using the chaos particle swarm optimization-based back propagation neural network (CPSO-BPNN) model. …”
Get full text

Smart Agile Prioritization and Clustering: An AI-Driven Approach for Requirements Prioritization by Aya M. Radwan, Manal A. Abdel-Fattah, Wael Mohamed

“…This paper proposes Smart Agile Prioritization and Clustering (SAPC), an AI-driven approach that enhances requirements prioritization by leveraging Natural Language Processing (NLP), BERT embeddings, graph-based dependency modeling, and optimization techniques. The proposed model extracts and processes textual requirements, constructs a dependency graph to model interrelations, and applies PageRank to compute requirement importance. …”
Get full text

Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images by Jamal Alsamri, Hamed Alqahtani, Ali M. Al-Sharafi, Abdulbasit A. Darem, Khalid Nazim, Abdul Sattar, Menwa Alshammeri, Ahmad A. Alzahrani, Marwa Obayya

“…Finally, the CADHDD-SFLNHM model implements the pelican optimization algorithm (POA) method to fine-tune the hyperparameters involved in the CNN-BiGRU-A method. …”
Get full text

Automated Classification and Identification of Non-Functional Requirements in Agile-Based Requirements Using Pre-Trained Language Models by Abdulrahim Alhaizaey, Majed Al-Mashari

“…In addition, thorough experiments on hyperparameter optimization were employed using Bayesian hyperparameter optimization to obtain the combination of hyperparameters that best correlated with the aim of enhancing each model’s performance. …”
Get full text

Separation Method for Installation Eccentricity Error of Workpiece by Guanyao Qiao, Chunyu Zhao, Huihui Miao, Ye Chen

“…This work solves the challenge of separating the eccentricity error of a workpiece installation from the first harmonic of radial runout error of the spindle, which has a crucial impact on improving the machining quality of the workpiece. Firstly, a mathematical model for the synthesized elliptical motion for spindle vibration and eccentricity error is established. …”
Get full text

AI-aided short-term decision making of rockburst damage scale in underground engineering by Chukwuemeka Daniel, Shouye Cheng, Xin Yin, Zakaria Mohamed Barrie, Yucong Pan, Quansheng Liu, Feng Gao, Minsheng Li, Xing Huang

“…This study investigates the effectiveness of ensemble machine learning models optimized through Bayesian optimization (BO) in predicting rockburst damage scales. …”
Get full text

Development of a Heat Transfer Model for a Free Double Piston and Identification of Thermal Management Challenges by Konstantinos Fotis, Zinon Vlahostergios, Dimitrios Misirlis, Kyros Yakinthos

Get full text

Prediction of Breakdown Voltage of Long Air Gaps Under Switching Impulse Voltage Based on the ISSA-XGBoost Model by Zisheng Zeng, Bin Song, Shaocheng Wu, Yongwen Li, Deyu Nie, Linong Wang

“…In addition, the ISSA-XGBoost model was compared with traditional machine learning models and other optimization algorithms. …”
Get full text

Evaluation of Manufacturing Accuracy in Merlon Fracture Models Fabricated by Vat Photopolymerization 3D-Printing Technologies by Hee-jung Lee, Chang-sub Jeong, Joon-mo Moon, Ji-myung Bae, Eun-joo Choi, Seung-han Oh

“…The Merlon fracture model is used to assess dimensional precision and machining accuracy. …”
Get full text

Examining human–AI collaboration in hybrid intelligence learning environments: insight from the Synergy Degree Model by Xinmei Kong, Haiguang Fang, Wenli Chen, Jianjun Xiao, Muhua Zhang

“…Abstract The integrating AI into teaching and learning has the potential to transform traditional classroom environments into hybrid intelligence learning environments, whereby human teachers and AI teachers (educational robots) work together synergistically to enhance students’ learning processes and outcomes. To understand and optimize the synergistic effect of human–AI collaboration in hybrid intelligence learning environments, this study proposes a human–AI synergy degree model (HAI-SDM). …”
Get full text

Sustainability Meets AI: The Potential of Coupling Advanced Materials Science with Life Cycle Assessment for Industry Commons by Panagiotis Kolozis, Michalis Galatoulas, Anastasia Gkika, Elias Koumoulos

“…A Random Forest model predicted LCA/LCC outcomes, facilitating real-time, sustainability-driven decisions. …”
Get full text

Artificial intelligence in suicide prevention: Utilizing deep learning approach for early detection by Vikas Gaur, Gaurav Maggu, Khushboo Bairwa, Suprakash Chaudhury, Sana Dhamija, Tahoora Ali

Get full text

Intelligent prediction and oriented design of high-hardness high-entropy ceramics by Anzhe Wang, Jicheng Liu, Linwei Guo, Kejie Qu, Haishen Xie, Yawei Li, Bin Du

“…This achievement is attributed to three key innovations: the construction of the feature space based on the Pearson correlation coefficient and genetic algorithm, along with algorithm selection and optimization through hyperparameter tuning; the novel combination of reduced-dimensionality component compositions with atomic/precursor descriptors, achieving a model R2 value of up to 0.898; the optimization of constituent elements using genetic algorithm and principal component analysis, providing direct guidance for the design of high-hardness high-entropy ceramics. …”
Get full text

Multi-objective combinatorial methodology for nuclear reactor site assessment: A case study for the United States by Omer Erdem, Kevin Daley, Gabrielle Hoelzle, Majdi I. Radaideh

“…These results underscore the potential of integrating machine learning and optimization techniques to transform nuclear siting, paving the way for a cost-effective and sustainable energy future.…”
Get full text

From Patterns to Predictions: Spatiotemporal Mobile Traffic Forecasting Using AutoML, TimeGPT and Traditional Models by Hassan Ayaz, Kashif Sultan, Muhammad Sheraz, Teong Chee Chuah

“…Our findings underscore the strengths of modern predictive models in capturing complex traffic behaviors and demonstrate their value in resource planning, congestion management and overall network optimization. …”
Get full text

Development and benchmarking of a thermal lumped model for the magnetron injection gun of the MW-power ITER European gyrotron by A. Antonione, R. Bertazzoni, G. Carannante, K. Cindric, M. Ferrari, A. Leggieri, F. Sanchez, G. De Tommasi

“…In this paper the model parameters are identified by using a Particle Swarm Optimization algorithm on experimental data and the model validation is finally carried out on a dedicated dataset, aiming at providing a tool to design and to be integrated into the control system of the machine.…”
Get full text

Principles of creating a digital twin prototype for the process of alkylation of benzene with propylene based on a neural network by K. G. Kichatov, T. R. Prosochkina, I. S. Vorobyova

Get full text

Hybrid deep learning and isogeometric analysis for bearing capacity assessment of sand over clay by Toan Nguyen-Minh, Tram Bui-Ngoc, Jim Shiau, Tan Nguyen, Trung Nguyen-Thoi

“…Notably, the WOA-DNN model outperforms conventional ML techniques, offering a robust and accurate prediction tool. …”
Get full text