Gradient-based optimization for parameter identification of lithium-ion battery model for electric vehicles by Motab Turki Almousa, Mohamed R. Gomaa, Mostafa Ghasemi, Mohamed Louzazni

“…The findings were contrasted to those from various algorithms, such as whale optimization algorithm, multi-verse optimizer, sine cosine algorithm, arithmetic optimization algorithm, particle swarm optimization, red kite optimization algorithm, tree-seed algorithm, and white shark optimizer. …”
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From Pairwise Comparisons of Complex Behavior to an Overall Performance Rank: A Novel Alloy Design Strategy by Rafael Herschberg, Lisa Rateau, Laure Martinelli, Fanny Balbaud-Célérier, Jean Dhers, Anna Fraczkiewicz, Gérard Ramstein, Franck Tancret

“…The obtained ranking is later fitted with respect to the alloy’s composition by a Gaussian process. The predictive power of the method is demonstrated in the case of the resistance of metallic materials to molten salt corrosion and wear. …”
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The feasibility of endoscopic stapes surgery: A three‐dimensional planning method by Maaike Jellema, Mijs Buter, Esther E. Blijleven, Koen Willemsen, H. Chien Nguyen, Robert J. Stokroos, Inge Wegner, Henricus G. X. M. Thomeer

“…Finally, the outcomes of the pre‐operative planning and the actual procedure were directly compared to evaluate the algorithm's accuracy and usability. Results The preoperative planning method achieved an accuracy rate of 70% in predicting the need for scutum removal. …”
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Mixed Gas Detection and Temperature Compensation Based on Photoacoustic Spectroscopy by Sun Chao, Hu Runze, Liu Niansong, Ding Jianjun

“…Experimental results show that, compared to the traditional SVM algorithm, the KNN-SVM algorithm performs better in gas classification prediction, with an accuracy rate of 99.167% and an AUC indicator of 99.375%, enhancing the accuracy of gas detection. …”
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Short-term Power Load Forecasting Method of Data Center Considering PUE by WU Jin-song, ZHANG Shao feng, XU Xiang-min, LI Shu-tao, HUANG Yong, LIAO Xiao

“…Therefore, the influence of PUE is considered in the prediction model, and the adaptive moment estimation algorithm is used for deep learning. …”
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A vehicular network–based intelligent transport system for smart cities by Tayyaba Zaheer, Asad Waqar Malik, Anis Ur Rahman, Ayesha Zahir, Muhammad Moazam Fraz

“…In developed countries, specialized sensors are deployed to gather traffic information to predict traffic patterns. Any traffic updates are shared with the commuters via the Internet. …”
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A Review of Abnormal Crowd Behavior Recognition Technology Based on Computer Vision by Rongyong Zhao, Feng Hua, Bingyu Wei, Cuiling Li, Yulong Ma, Eric S. W. Wong, Fengnian Liu

“…Its goal is to use computer vision technology and abnormal behavior detection models to accurately perceive, predict, and intervene in potential abnormal behaviors of the crowd and monitor the status of the crowd system in public places in real time, to effectively prevent and deal with public security risks and ensure public life safety and social order. …”
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Distributed hybrid consensus–based square-root cubature quadrature information filter and its application to maneuvering target tracking by Jun Liu, Yu Liu, Kai Dong, Ziran Ding, You He, Qichao Li

“…The proposed hybrid consensus–based square-root cubature quadrature information filter exploits fifth-order spherical simplex-radial quadrature rule to tackle system nonlinearities and incorporates a novel measurement update strategy into the hybrid consensus filtering framework, which takes the predicted measurement error into account and hence produces more accurate estimates. …”
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Software Supporting the Visualization of Hazardous Substance Emission Zones During a Fire at an Industrial Enterprise by Yuri Matveev, Fares Abu-Abed, Olga Zhironkina, Sergey Zhironkin

“…The possible chain-like nature of fires and explosions of containers with toxic substances inside increases the importance of predicting changes in hazardous zone parameters in real time. …”
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Optimization of engine parameters and emission profiles through bio-additives: Insights from ANFIS Modeling of Diesel Combustion by Abbas Rohani, Javad Zareei, Kourosh Ghadamkheir, Seyed Alireza Farkhondeh

“…Additionally, an Adaptive Neuro-Fuzzy Inference System (ANFIS) model was developed to predict combustion characteristics, engine parameters, and exhaust gas emissions. …”
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Enhanced Fall Detection Using YOLOv7-W6-Pose for Real-Time Elderly Monitoring by Eugenia Tîrziu, Ana-Mihaela Vasilevschi, Adriana Alexandru, Eleonora Tudora

“…This approach, integrated into the NeuroPredict platform developed by our team, advances fall detection technology, supporting better care and safety for older adults.…”
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A CART-Based Model for Analyzing the Shear Behaviors of Frozen–Thawed Silty Clay and Structure Interface by Fengpan Zhu, Bo Wang, Zhiqiang Liu

“…The CART-based model offers a scientific basis for predicting the shear behavior of the frozen–thawed soil–structure interface.…”
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Application of Machine Learning and Multi-Dimensional Perception in Urban Spatial Quality Evaluation: A Case Study of Shanghai Underground Pedestrian Street by Tianning Yao, Yao Xu, Liang Sun, Pan Liao, Jin Wang

“…It then gathers multidimensional perception data from selected locations and ultimately analyses and predicts the results employing machine learning techniques, specifically Random Forest and XGBoost. …”
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A Numerical Laboratory for Simulation of Flanged Reinforced Concrete Shear Walls by Alireza Khaloo, Mohammad Tabiee, Hatef Abdoos

“…In order to validate FlashLab, this paper numerically simulates T-, H-, and L-shaped RC shear walls and compares the results to the experimental data, indicating good agreement between the numerical and experimental results to an extent that the proposed numerical laboratory is capable of predicting the backbone curve with an accuracy more than 90 percent. …”
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An IoT-Driven Real-Time Skin Disease Detection System using Machine Learning by Aliya Aftab, Dr.Hina Sattar, Muhammad Farhan Aslam, Touseef Hussain, Syeda Sitara Waseem

“…IoT will measure body temperature, and a deep learning algorithm and CNN algorithm predict the diseases. The output is provided on the GUI as an Android application, in order to help them understand whether they have skin diseases and allergies early. …”
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Neural Networks in Forecasting Disease Dynamics by A. G. Hasanov, D. G. Shaybakov, S. V. Zhernakov, A. M. Men’shikov, F. F. Badretdinova, I. F. Sufiyarov, J. R. Sagadatova

“…The best convergence of the network learning process is provided by the quasi-Newton and conjugated gradient algorithms. In order to assess the effectiveness of the proposed neural network in predicting the dynamics of inflammation, a comparative analysis was carried out using a number of conventional methods, such as exponential smoothing, moving average, least squares and group data handling.Conclusion.The proposed neural network based on approximation and extrapolation of variations in the patient’s medi‑ cal history over fixed time window segments (within the ‘sliding time window’) can be successfully used for forecasting the development and outcome of erysipelas.…”
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Healthcare Economics-Vital Threat Detection System Efficiency: A Business Process Analysis Methodology by Salma Elhag, Amal Alghamdi, Amal Alahmari, Abeer Alharbi

“…The data is sent to the cloud, where it is stored and analyzed using artificial intelligence (AI) algorithms to predict critical health conditions. When any abnormalities are detected, immediate alerts are sent to family members or caregivers via mobile applications, enabling a quick response. …”
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Estimating Aggregate Capacity of Connected DERs and Forecasting Feeder Power Flow With Limited Data Availability by Amir Reza Nikzad, Amr Adel Mohamed, Bala Venkatesh, John Penaranda

“…The method is tested using a North American utility feeder data, achieving an average accuracy of 95.56% for forecasting aggregate load power, 93.70% for feeder flow predictions, and 97.53% for estimating the aggregate capacity of DERs.…”
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Analysis of State-of-Charge Estimation Methods for Li-Ion Batteries Considering Wide Temperature Range by Yu Miao, Yang Gao, Xinyue Liu, Yuan Liang, Lin Liu

“…Accurate state-of-charge (SOC) estimation is critical for optimizing battery performance, ensuring safety, and predicting battery lifetime. However, SOC estimation faces significant challenges under extreme temperatures and complex operating conditions. …”
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Toward Street‐Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High‐Resolution Weather Radar Data by Pierfranco Costabile, Carmelina Costanzo, John Kalogiros, Vasilis Bellos

“…This approach paves the way for the development of new operational systems focused on impact‐based flash‐floods nowcasting, wherein hydrodynamic simulations directly model the spatial and temporal variability of measured or predicted rainfall on impacts even at a street scale. …”
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