Optimizing Photovoltaic Power Prediction Using Computational Methods and Artificial Neural Networks by Cempaka Amalin Mahadzir, Ahmad Fateh Mohamad Nor, Siti Amely Jumaat, Noor Syahirah Ahmad Safawi

“…By comparing the Mean Squared Error (MSE) of four different values of derating factor due to dirt which are 0.8, 0.88, 0.9 and 0.98 in ANN predictions comprehend with 4 input layers and 10 hidden layers. …”
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Optimization of Xanthan Gum and Sorbitol Levels in the Mycophenolate Mofetil Powder for Oral Suspension by Amin Umrani, Homa Faghihi, Zohreh Mohammadi, Parastoo Mirzabeigi, Hamed Montazeri Ghods, Ali Rastegari

“…Optimized sample composed of 16.69 g sorbitol and 68.81 mg xanthan gum. …”
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Optimizing Injection Molding for Propellers with Soft Computing, Fuzzy Evaluation, and Taguchi Method by M. Hedayati-Dezfooli, Mehdi Moayyedian, Ali Dinc, Mostafa Abdrabboh, Ahmed Saber, A. M. Amer

“…The Fuzzy-TOPSIS method, in conjunction with ANN, is employed to ascertain the optimal levels of the selected parameters. The margin of error between the chosen optimization methods is found to be less than one percent, underscoring their suitability for injection molding optimization. …”
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Research on interactive optimization technology in music education games based on EMD-RNN by Xiaohang Yang

“…Based on the EMD-RNN model, this study explores its application of interactive optimization technology in music educational games. The EMD (Empirical Mode Decomposition) method adaptively decomposes audio signals into multiple eigenmode functions, which makes the processing of non-stationary signals more accurate, especially suitable for intonation and rhythm analysis in music teaching. …”
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Solving Spatial Optimization Problems via Lagrangian Relaxation and Automatic Gradient Computation by Zhen Lei, Ting L. Lei

“…Spatial optimization is an integral part of GIS and spatial analysis. …”
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Machine-Learning-Driven Approaches for Assessment, Delegation, and Optimization of Multi-Floor Building by Abtin Baghdadi, Harald Kloft

“…This study presents a novel integrated framework for the structural analysis and optimization of multi-floor buildings by combining validated theoretical models with machine learning and evolutionary algorithms. …”
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Optimized bio-signal reconstruction and watermarking via enhanced fractional orthogonal moments by Gaber Hassan, Khalid M. Hosny, Islam S. Fathi

“…Many fields, including signal analysis and watermarking, have relied heavily on such moments. …”
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Parameter Calculation and Rotor Structure Optimization Design of Solid Rotor Induction Motors by Hao Xu, Jinghong Zhao, Sinian Yan

“…The theoretical analysis is verified by finite element simulation and prototype experiment, and the results show that the electromagnetic parameters of solid rotor induction motors with different rotor structures can be accurately calculated using the universal magnetic field analytical model and the universal equivalent circuit model with an error within 5.8%. …”
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Optimizing public health management with predictive analytics: leveraging the power of random forest by Hongman Wang, Yifan Song, Yifan Song, Hua Bi

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Optimizing Photovoltaic Panel Performance: A Comparative Study of Meta-Heuristic Algorithms by M. Sundar Rajan

“…Various optimization techniques exist, including intelligent methods that incorporate functions, constraints, contributions, mathematical models, and analysis methods. …”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). …”
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The impact of tractor drawbar height on performance and optimization using response surface methodology by Ali Yavuz Şeflek, Nuri Orhan, Mete Özkan

“…Data were collected at different tractor forward speeds and performance parameters were modeled and optimized using Response Surface Methodology (RSM), a statistical approach widely used for multi-factor optimization. …”
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Optimizing mRNA Vaccine Degradation Prediction via Penalized Dropout Approaches by Hwai Ing Soon, Azian Azamimi Abdullah, Hiromitsu Nishizaki, Latifah Munirah Kamarudin

“…A novel tetramer-label encoding approach (4-mer-lbA) was proposed, integrating biological relevance with data-driven analysis to enhance predictive accuracy. To further optimize model performance, two advanced hyperparameter optimization (HPO) techniques—Dropout-Enhanced Technique (DEet) and Hyperparameter Optimization Algorithm Penalizer (HOPeR)—are proposed to mitigate overfitting, address inefficiencies in conventional HPO algorithms (HPOAs), and accelerate model convergence. …”
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Edge-optimized multimodal cross-fusion architecture for efficient crop disease detection by Thomas Kinyanjui Njoroge, Kelvin Mugoye Shindu, Rachael Kibuku

“…Traditional diagnostic methods, such as manual inspections, are often inefficient and error-prone. Existing deep learning models (e.g., ResNet50, Inception V3) struggle with computational inefficiency and poor generalizability in real-world farming contexts. …”
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Study on Optimization of Rice-Drying Process Parameters and Directional Regulation of Nutrient Quality by Jinquan Li, Kezhen Chang, Jun Yin, Yi Jin, Xiaokang Yi, Zhongjie Zhang, Yichuan He, Qiaonan Yang, Zhihui Tang, Xiaoyu Liu, Wenfu Wu

“…The contents of protein, fat, amylose and amylopectin were 8.47 g/100 g, 1.97 g/100 g, 15.33 g/100 g and 60.50 g/100 g, respectively. The relative error of the verification test was 4.17%. The optimized process can effectively maintain the nutritional quality of rice and improve drying efficiency. …”
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Knowledge embedding and interpretable machine learning optimize comprehensive benefits for water treatment by Yu-Qi Wang, Wenchong Tian, Hao-Lin Yang, Yun-Peng Song, Jia-Ji Chen, Qiong-Ying Xu, Wan-Xin Yin, Le-Qi Ding, Xi-Qi Li, Han-Tao Wang, Ai-Jie Wang, Hong-Cheng Wang

“…Random forest (RF) has the best performance among the eight methods with a percentage error of 2.53% and a coefficient of determination of 0.9922. …”
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Leveraging machine learning to optimize cooling tower efficiency for sustainable power generation by M. A. Mujtaba, Muhammad Adeel Munir, Muhammad Akhtar, Bilal Mahmood, Talha Ansar, Zeeshan Khawar, Shayan Khalid, Abdul Basit, Saud Jamil, M. A. Kalam, Fayaz Hussain, Chiranjib Bhowmik

“…After tuning the hyperparameters, an R-square score of 0.983 and a root mean squared error of 0.57 are achieved. Afterwards, a sensitivity analysis of relative humidity (%), turned out to be the most important feature, with a contribution of 12%. …”
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AUTOMATION OF OPTIMAL IDENTIFICATION OF DYNAMIC ELEMENT TRANSFER FUNCTIONS IN COMPLEX TECHNICAL OBJECTS BASED ON ACCELERATION CURVES by A. Yu. Alikov, M. A. Kovaleva, A. L. Rutkovskiy, N. V. Tedeeva

“…On the basis of the analysis of its advantages and disadvantages, a modified method is proposed that allows the structure and parameters of the transfer function to be identified according to the experimental acceleration curve, as well as the choice of optimal numerical values of those parameters obtained for minimising errors in the approximation of the experimentally obtained acceleration curves.Conclusion. …”
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Enhancing Stock Price Forecasting With a Hybrid SES-DA-BiLSTM-BO Model: Superior Accuracy in High-Frequency Financial Data Analysis by Talabathula Jayanth, A. Manimaran, G. Siva

“…Stock price forecasting is a critical component of financial market analysis and plays a key role in formulating investment strategies, affecting a wide range of stakeholders. …”
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Optimized SPR-PCF sensor for sucrose detection inspired by vertical pupil geometry by Mohammad Reza Khodatars Dashtmian, Vahid Fallahi, Mahmood Seifouri, Saeed Olyaee

“…To ensure this, we have applied the Nelder-Mead algorithm for precise optimization of the structural parameters. For the analysis of this structure, the finite element method based on the mode solver has been used. …”
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