Exploring Procedural Content Generation of Environments for Virtual Museums: A Mixed-Initiative Approach by Claudio Rubio, Nicolas A. Barriga, Ben Ingram, Huizilopoztli Luna-García, Felipe Besoain

Get full text

探討強化學習演算法之素材推薦機制與AI學習履歷之學習者感知 Learner Perceptions of AI-Powered Learning Portfolios and Personalized Material Recommendation Mechanisms in Reinforcement Learning Algorithms... by 曾建維 Jian-Wei Tzeng, 黃天麒 Tien-Chi Huang, 薛承祐 Cheng-Yu Hsueh, 廖英淞 Ying-Song Liao

“…Consistent percentile rank increases following practice question completion suggest the system’s capacity to deliver personalized recommendations on the basis of individual differences, thereby facilitating concept-specific feedback and adaptive learning. …”
Get full text

Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

“…The proposed optimized MARL framework dynamically learns optimal parameter adjustments through a reward mechanism, minimizing localization error and its variability even under dynamic network conditions. The GJO algorithm fine-tunes the hyperparameters of MARL to improve generalization across different WSN configurations. …”
Get full text

Construction of a risk prediction model for pulmonary infection in patients with spontaneous intracerebral hemorrhage during the recovery phase based on machine learning by Jixiang Xu, Yuan Li, Fumin Zhu, Fumin Zhu, Xiaoxiao Han, Liang Chen, Yinliang Qi, Yinliang Qi, Xiaomei Zhou, Xiaomei Zhou

“…Seven ML algorithms were employed to build predictive models, with performance evaluated based on the area under the receiver operating characteristic (AUC) curve, sensitivity, specificity, and accuracy. …”
Get full text

Enhanced AdaBoostM1 with Multilayer Perceptron for Stock Price Prediction by Rebwar Mala Nabi, Soran AB. Saeed, Habibollah Haron

“…Among the predictive models, various adaptations of the AdaBoostM1 algorithm have been applied to stock market prediction, either by tuning parameters or experimenting with different base learners. …”
Get full text

Intelligent power control strategy based on self-tuning fuzzy MPPT for grid-connected hybrid system by H. Chaib, S. Hassaine, Y. Mihoub, S. Moreau

“…Unlike conventional methods that rely on logical switches, this intelligent strategy utilizes fuzzy rules adapted to different operating modes for more sophisticated energy control. …”
Get full text

Performance assessment of basalt fibre concrete under freeze-thaw cycles using hybrid long short-term memory models by Qingguo Yang, Honghu Wang, Qigui Yi, Liuyuan Zeng, Rui Xiang, Longfei Guan, Jiawei Cheng, Keling Chen, Yunhao Li

“…By integrating self-conducted experimental data and referenced datasets, a diverse experimental database was constructed. Improved algorithms, namely Asynchronous Learning Particle Swarm Optimization (AsyLnCPSO) and Hybrid Genetic Algorithm-based Particle Swarm Optimization (GA-HIDMS-PSO), were paired with LSTM neural networks to systematically evaluate their adaptability and effectiveness in predicting the performance of basalt fiber-reinforced concrete under freeze-thaw conditions. …”
Get full text

Feature extraction and fault diagnosis of gearbox based on ICEEMDAN, MPE, RF and SVM by DING Xiaofeng, ZHANG Yuhua

“…Finally, the importance of such features was evaluated by the RF algorithm, and the sensitive features with high importance were selected to form the optimal feature subset as the input to SVM for fault pattern recognition. …”
Get full text

Can Integrating SoC Management in Economic Dispatch Enhance Real-Time Operation of a Microgrid? by Alessia Cagnano

“…To enable real-time adaptability, the methodology employs a Lyapunov-based optimization algorithm combined with a sensitivity analysis, ensuring rapid convergence to optimal solutions, even under rapidly changing conditions. …”
Get full text

Building an international precision medicine platform trial for the acute respiratory distress syndrome (ARDS): an expert consensus project report by Kiran Reddy, Neil Aggarwal, Narges Alipanah-Lechner, Djillali Annane, David B Antcliffe, Daphne Babalis, J Kenneth Baillie, Abigail Beane, Lieuwe DJ Bos, Aidan Burrell, Carolyn S Calfee, Kiki Cano-Gamez, Victoria R Cornelius, Mary Cross, Emma Davenport, Lorenzo del Sorbo, Laura Esserman, Eddy Fan, Vito Fanelli, Niall D Ferguson, D Clark Files, Christoph Fisser, Shigeki Fujitani, Ewan C Goligher, Anthony C Gordon, Giacomo Grasselli, Fergus Hamilton, Rashan Haniffa, Andrea Haren, Daniel JR Harvey, Leanne M Hays, Anna Heath, Nicholas Heming, Susanne Herold, Tim Hicks, Nao Ichihara, Vinod Jaiswal, Jun Kataoka, Julian C Knight, Patrick R Lawler, Kathleen Liu, John C Marshall, David M Maslove, Michael A Matthay, Daniel F McAuley, Nuala J Meyer, Jonathan A Millar, Holger Müller-Redetzky, Alistair Nichol, John Norrie, Marlies Ostermann, Andrew Owen, Cecilia M O’Kane, Dhruv Parekh, Rachel Phillips, Duncan Richards, Bram Rochwerg, Anthony J Rostron, Hiroki Saito, Romit J Samanta, Vittorio Scaravilli, Wesley Self, Manu Shankar-Hari, A John Simpson, Pratik Sinha, Marry R Smit, Jonathan Stewart, B Taylor Thompson, István Vadász, Ed Waddingham, Steve Webb, Graham Wheeler, D Martin Witzenrath, Mark M Wurfel, Thomas R Martin

Get full text

The Specialist’s Paradox: Generalist AI May Better Organize Medical Knowledge by Carlo Galli, Maria Teresa Colangelo, Marco Meleti, Elena Calciolari

Get full text

Prediction of Current and Future Distributions of Chalcophora detrita (Coleoptera: Buprestidae) Under Climate Change Scenarios by Arif Duyar, Muhammed Arif Demir, Mahmut Kabalak

Get full text

Eyes on nature: Embedded vision cameras for terrestrial biodiversity monitoring by Kevin F. A. Darras, Marcel Balle, Wenxiu Xu, Yang Yan, Vincent G. Zakka, Manuel Toledo‐Hernández, Dong Sheng, Wei Lin, Boyu Zhang, Zhenzhong Lan, Li Fupeng, Thomas C. Wanger

Get full text

Wellcounter: Automated high‐throughput phenotyping for aquatic microinvertebrates by Claus‐Peter Stelzer, Dominique Groffman

Get full text

Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization by Serdar Ekinci, Davut Izci, Veysel Gider, Laith Abualigah, Mohit Bajaj, Ievgen Zaitsev

“…The results show that QIO-RPIDD2 achieves superior performance, adapts quickly to different reference temperatures and performs excellently on key performance indicators. …”
Get full text

A Comparison of Inversion Methods for Surrogate‐Based Groundwater Contamination Source Identification With Varying Degrees of Model Complexity by Zhenbo Chang, Zhilin Guo, Kewei Chen, Zibo Wang, Yang Zhan, Wenxi Lu, Chunmiao Zheng

“…Each method has its own advantages and disadvantages under specific site conditions. To evaluate the applicability of these methods, we chose one representative inversion algorithm from each category, namely the Improved Butterfly Optimization Algorithm (IBOA) for simulation optimization, the Ensemble Smoother with Multiple Data Assimilation (ES‐MDA) for data assimilation, and the DiffeRential Evolution Adaptive Metropolis with a Snooker Update and Sampling from a Past Archive (DREAM(ZS)) for Bayesian inference. …”
Get full text

Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…However, the difference was slight. Since the output of the multi-objective algorithm was a Pareto solution set, four indices, uniformity, convergence, diversity, and dominance, were selected to evaluate the distribution in the solution space and to compare the solution results of each algorithm. …”
Get full text

Peningkatan Akurasi Metode Weighted Fuzzy Time Series Forecasting Menggunakan Algoritma Evolusi Differensial dan Fuzzy C-Means by Agus Fachrur Rozy, Solimun Solimun, Ni Wayan Surya Wardhani

“…The DE algorithm works by seeking the best solution in a complex parameter space through iterations and performance evaluations, thereby significantly enhancing the performance of the forecasting model. …”
Get full text

Prediction of Drifter Trajectory Using Evolutionary Computation by Yong-Wook Nam, Yong-Hyuk Kim

“…In contrast to existing numerical models that use the Lagrangian method, we used an optimization algorithm to predict the trajectory. As the evaluation measure, a method that gives a better score as the Mean Absolute Error (MAE) when the difference between the predicted position in time and the actual position is lower and the Normalized Cumulative Lagrangian Separation (NCLS), which is widely used as a trajectory evaluation method of drifters, were used. …”
Get full text

Generative design optimization of tree distribution for enhanced thermal comfort in communal spaces with special reference to hot arid climates by Ahmed Maged, Aly Abdelalim, Abdelaziz Farouk A. Mohamed

“…These applications, help designers in solving multi-objective design quandaries through the generation and evaluation of numerous design options. Therefore, this study explores the efficiency of generative design tools in optimizing tree distribution based on mutation evolution to enhance outdoor thermal comfort, providing a dynamic, iterative approach that adapts to diverse urban morphologies. …”
Get full text