Advanced hybrid machine learning based modeling for prediction of properties of ionic liquids at different temperatures by Saud Bawazeer

“…The harmony search (HS) algorithm was employed as an optimization algorithm to find the best hyper-parameters combination by minimizing the error. …”
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A Time-Segmented SAI-Krylov Subspace Approach for Large-Scale Transient Electromagnetic Forward Modeling by Ya’nan Fan, Kailiang Lu, Juanjuan Li, Tianchi Fu

“…The paper further explores how dividing the off-time and optimizing parameters for each time interval can enhance computational efficiency. …”
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Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In order to solve the mixed integer nonlinear problem (MINLP), a data offloading selection strategy based on proximity discovery and an iterative method-based resource allocation algorithm (IRA) are proposed. In addition, the closed-form solutions of the optimized variables are obtained. …”
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A Lightweight Method for Road Defect Detection in UAV Remote Sensing Images with Complex Backgrounds and Cross-Scale Fusion by Wenya Zhang, Xiang Li, Lina Wang, Danfei Zhang, Pengfei Lu, Lei Wang, Chuanxiang Cheng

“…Moreover, the CAA attention mechanism is employed to strengthen the model’s global feature extraction abilities; (2) a cross-scale feature fusion strategy known as GFPN is developed to tackle the problem of diverse target scales in road damage detection; (3) to reduce computational resource consumption, a lightweight detection head called EP-Detect has been specifically designed to decrease the model’s computational complexity and the number of parameters; and (4) the model’s localization capability for road damage targets is enhanced by integrating an optimized regression loss function called WiseIoUv3. …”
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Intelligent Battery Management in a Hybrid Photovoltaic Using Fuzzy Logic System by Jo-Ann V. Magsumbol, Argel A. Bandala, Alvin B. Culaba, Edwin Sybingco, Ryan Rhay P. Vicerra, Raouf Naguib, Elmer P. Dadios

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A Novel Automated Decision-Making Process for Analysis of Ions and Organic Materials in Drinking Water by Javanbakht T.

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Improvement of Network Traffic Prediction in Beyond 5G Network using Sparse Decomposition and BiLSTM Neural Network by Rihab Abdullah Jaber Al Hamadani, Mahdi Mosleh, Ali Hashim Abbas Al-Sallami, Rasool Sadeghi

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Enhanced Convolutional Neural Network for Accurate Crop Recommendation System on Climate Data by Adnan Myasar M., AI_Sadi Hafidh l., Abhilash Pideka Kundil

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Simulation for non-homogeneous transport equation by Nyström method by Luana Lazzari, Esequia Sauter, Fábio Souto De Azevedo

“…This formulation allows us to use any function to describe both scattering cross section and total cross section. The algorithm is implemented in C language with the use of routines of GNU scientific library and computational techniques for code optimization. …”
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A single-snapshot inverse solver for two-species graph model of tau pathology spreading in human Alzheimer’s disease by Zheyu Wen, Ali Ghafouri, George Biros, the Alzheimer’s Disease Neuroimaging Initiative (ADNI)

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Visual analysis of multi-subject association patterns in high-dimensional time-varying student performance data by Lianen Ji, Ziyi Wang, Shirong Qiu, Guang Yang, Sufang Zhang

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RDW-YOLO: A Deep Learning Framework for Scalable Agricultural Pest Monitoring and Control by Jiaxin Song, Ke Cheng, Fei Chen, Xuecheng Hua

“…This study introduces RDW-YOLO, an improved pest detection algorithm based on YOLO11, featuring three key innovations. …”
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Beam Tracking in Switched-Beam Antenna System for V2V Communication by Settawit Poochaya, Peerapong Uthansakul

“…This paper presents the proposed switched beam antenna system for V2V communication including optimum antenna half power beamwidth determination in urban road environments. SQP optimization method is selected for the computation of optimum antenna half power beamwidth. …”
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OR-FCOS: an enhanced fully convolutional one-stage approach for growth stage identification of Oudemansiella raphanipes by Runze Fang, Huamao Huang, Nuoyan Guo, Haichuan Wei, Shiyi Wang, Haiying Hu, Ming Liu

“…Abstract Accurate identification of Oudemansiella raphanipes growth stages is crucial for understanding its development and optimizing cultivation. However, deep learning methods for this task remain unexplored. …”
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Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping by Yong Dai, Ming Zhao

“…In addition, we propose an adaptive local data association (Range-SLAM) scheme to improve the computational efficiency for the algorithm of the nearest neighbor (NN) data association in the iteration of the RBPF prediction. …”
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Towards precision agriculture: metaheuristic model compression for enhanced pest recognition by Sana Parez, Norah Saleh Alghamdi, Tahir Mahmood, Waseem Ullah, Muhammad Attique Khan, Taha Houda, Naqqash Dilshad

“…To reduce model complexity and improve deployment feasibility, a metaheuristic optimization algorithm was incorporated that significantly reduces computational overhead without compromising performance. …”
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Integration of Artificial Neural Network in a IEEE 5 BUS System by T. L. Makosso, A. Almaktoof, K. Abo-Al-Ez

“…In the context of Artificial Neural Networks (ANNs), the Levenberg-Marquardt (LM) algorithm is an extensively utilized optimization method. …”
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High resolution satellite imaging 0.5U-size freeform telescope for CubeSat by Jacek Wojtanowski

“…The proposed design algorithm proved to be computationally efficient. It enabled to obtain the excellent imaging of the designed telescope, which from mathematical perspective becomes a challenging multi-variable optimization task, unattainable with the standard optimization procedures included in the commercial optical design software.…”
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Efficient Model Calibration Using Submodels by P. T. M. Vermeulen, G. M. C. M. Janssen, T. Kroon

“…As runtimes increase almost quadratically with the number of model cells, this makes the models ever more computationally demanding. This high computational demand introduces challenges for the history‐matching (calibration) process as this is an algorithmic process that needs hundreds or thousands of model‐runs to obtain the model sensitivities needed to estimate parameters. …”
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Intelligent routing for human activity recognition in wireless body area networks by Enas Selem Elmosallamy, Mohammed F. Soliman

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