Influence of Tire Parameters on Contact Patch and Axle Force Generation against Short Obstacles Using DOE Approach by Vikas Birajdar, Seyed Jamaleddin Mostafavi Yazdi, Madhu Kandampadath, Mohammad Behroozi, Javad Baqersad

“…This algorithm filters the geometries of uneven surfaces and must be seamlessly integrated with a rigid ring model. …”
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Super-Resolution Reconstruction From Multiple Defocused Infrared Images of Stationary Scene by Yuxing Mao, Benjiang Zhao, Dongmei Yan, Haiwei Jia

“…We have developed an image degradation model by analyzing optical lens imaging, using the particle swarm optimization algorithm to estimate the PSF of the HR image, and using compressed sensing theory to implement SRR based on the noncoherent characteristics of the defocused infrared images. …”
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Machine learning-based prediction of optimal antenatal care utilization among reproductive women in Nigeria by Jamilu Sani, Adeyemi Oluwagbemiga, Mohamed Mustaf Ahmed

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Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning by Jun Tan, Raoof Mohammed Radhi, Kimia Shirini, Sina Samadi Gharehveran, Zamen Parisooz, Mohsen Khosravi, Hossein Azarinfar

“…The proposed framework was evaluated through extensive simulations in a MATLAB environment, where it demonstrated remarkable improvements in system performance. The integration of Digital Twins allowed for precise real-time modeling of system behavior, while Deep Learning algorithms effectively identified and predicted faults. …”
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A study of high-resolution remote sensing image landslide detection with optimized anchor boxes and edge enhancement by Kun Wang, Ling Han, Juan Liao

“…Using the You Only Look Once v5 network (YOLOv5) in combination with the Gabor filter, its edge detection, detection anchor frame and small object detection scale are improved and optimized. The YOLOv5(ISODATA) model was finally established for landslide image detection by incorporating the edge control factor and four clustering algorithms (K-means, K-means + +, k-medoid, and Iterative Self-Organizing Data Analysis Techniques Algorithm (ISODATA) to evaluate the accuracy of the detection anchor frame and add small target large-scale sampling. …”
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An Assembled Feature Attentive Algorithm for Automatic Detection of Waste Water Treatment Plants Based on Multiple Neural Networks by Cong Li, Zhengchao Chen, Zhuonan Huang, Yue Shuai, Shaohua Wang, Xiangkun Qi, Jiayi Zheng

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Bayesian-optimized ensemble deep learning models for demand forecasting in the volatile situations: A case study of grocery demand during Covid-19 outbreaks by Nader AL Theeb, Hazem Smadi, Naser Al-qaydeh

“…Furthermore, using BO algorithm for hyperparameters tuning improved the forecasting accuracy. …”
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An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…The main objective of the proposed optimal weighting-based CNN-LSTM-SVM (OCLS) hybrid classifier is to simultaneously leverage the unique advantages of CNN in feature extraction from input signals, LSTM in modeling the sequential patterns of signals, SVM in classifying regular patterns, and especially the proposed weighting algorithm to optimally integrate the outputs of these components. …”
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Development of a cognitive blood glucose–insulin control strategy design for a nonlinear diabetic patient model by Dagher Khulood Eskander, Haggege Joseph

“…Additionally, the comparison results demonstrated that the suggested cognitive glucose–insulin control algorithm improved the time to reach a normal physiological blood glucose level by 10% compared to the fuzzy logic and the fractional-order proportional integral derivative (PID) control algorithms, by 25% compared to the type-2 fuzzy control algorithm, and by 6% compared to the PID-particle swarm optimization control algorithm.…”
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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…Moreover, understanding the relative importance and contribution of different waste properties to HHV prediction is critical for improving the model's predictive capability and optimizing the waste-to-energy (WTE) process. …”
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Flexible Demand Side Management in Smart Cities: Integrating Diverse User Profiles and Multiple Objectives by Nuno Souza e Silva, Paulo Ferrão

“…Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. …”
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Metaheuristic Prediction Models for Kerf Deviation in Nd-YAG Laser Cutting of AlZnMgCu1.5 Alloy by Arulvalavan Tamilarasan, Devaraj Rajamani

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State of charge estimation of lithium-ion batteries in an electric vehicle using hybrid metaheuristic - deep neural networks models by Zuriani Mustaffa, Mohd Herwan Sulaiman, Jeremiah Isuwa

“…This study proposes a novel approach for SoC estimation in BMW EVs by integrating a metaheuristic algorithm with deep neural networks. Specifically, teaching-learning based optimization (TLBO) is employed to optimize the weights and biases of the deep neural networks model, enhancing estimation accuracy. …”
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Low-cost Cascaded prototype for DC-DC converters for Renewable energy applications by Rerhrhaye Fathallah, Ennaciri Yassine, Rerhrhaye Badr, Lahlouh Ilyas, Khouili Driss, El Martaoui Chaymae, El Akkary Ahmed, Sefiani Nacer

“…The proposed prototype offers a cost-effective and highly efficient solution for implementing various Maximum Power Point Tracking (MPPT) algorithms and advanced control methods. …”
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Research on Cultivated Land Quality Assessment at the Farm Scale for Black Soil Region in Northeast China Based on Typical Period Remote Sensing Images from Landsat 9 by Meng Gao, Zhao Yang, Xiaoming Li, Hongmin Sun, Yanhong Hang, Boyu Yang, Yang Zhou

“…A case study at Shuanghe Farm in Northeast China shows that (1) compared to the BO-Stacking-TabNet model using vegetation indices as input, the BO-Stacking-TabNet model based on spectral reflectance as the input indicator achieved an improvement of 10.62% in Accuracy, 1.55% in Precision, 11.05% in Recall, and 10.18% in F1-score. (2) Compared to the original TabNet model, the BO-Stacking-TabNet model optimized by the two-step Stacking process and Bayesian optimization algorithm improved Accuracy by 2.13%, Precision by 12.59%, Recall by 1.83%, and F1-score by 2.19%. …”
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Addressing the Return Visit Challenge in Autonomous Flying Ad Hoc Networks Linked to a Central Station by Ercan Erkalkan, Vedat Topuz, Ali Buldu

“…This paper presents different approaches to efficiently directing UAVs and explains how heuristic algorithms can enhance our understanding and improve current methods for task assignments.…”
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An efficient cost calculation method for disparity estimation of stereo matching considering shadow occlusion by Hongjun Sha, Wei Yuan, Xunping Wang, Xiuliu Yuan, Shunichi Koshimura

“…To verify the optimization ability and transferability of MCSP, the MCSP cost is integrated into three classical disparity estimation algorithms respectively. …”
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Emergency evacuation paths for tank farm fires based on bi-objective dynamic planning by Guanbo Chou, Yili Duo, Jie Liu, Lin Sun, Yuyuan Zhang, Tie Sun

“…The BODP method includes both an equivalent rule proposed for the first time based on the linear weighting method, and an improved Dijkstra algorithm designed in this paper. …”
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Advancing Pile-Bearing Capacity Prediction with Meta-Heuristic Enhanced Specific ANFIS strategys by Zhongmiao Dang

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Numerical thermodynamic-economic study and machine learning-based optimization of an innovative biogas-driven integrated power plant combined with sustainable liquid CO2 and liquid... by Ruijia Yuan, Fan Shi, Azher M. Abed, Mohamed Shaban, Sarminah Samad, Ahmad Almadhor, Barno Abdullaeva, Mouloud Aoudia, Salem Alkhalaf, Samah G. Babiker

“…In industrial environments, it effectively optimizes energy use and production processes by examining various operational factors, which leads to cost reductions and improved efficiency via predictive maintenance and cohesive energy strategies. …”
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