Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons by Coulon Romain

“…While traditional methods such as the weighted mean and weighted median often fail to handle extreme values and non-Gaussian distributions, advanced techniques like the Monte Carlo Median (MCM) and Power Moderated Mean (PMM) offer improved robustness. …”
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Purchasing Prediction Using Machine Learning Algorithms for Optimizing Inventory Management by Reza Hamdi Prayetno, Rani Destika Purba, Kyrene Wirawan, Kelvin Sweet, Evta Indra

“…The LSTM method is used to predict spare parts stock with significant accuracy, demonstrated through evaluation metrics: Mean Absolute Error (MAE) 12%, Mean Squared Error (MSE) 2%, and Root Mean Square Error (RMSE) 15%. …”
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An Improved Adaptive Variable Step Size LMS Algorithm for Harmonic Detection by ZHANG Han

“…In order to improve the accuracy and tracking speed of harmonic current detection, an improved variable step-size LMS (least mean square ) algorithm was proposed based on LMS algorithm. …”
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Inverse versus convolution treatment planning algorithms for gamma knife radiosurgery by Marwa Ghanim, Siham Abdullah, Moneer Faraj, Nabaa Alazawy

“…The mean dose delivered was 15.86±3.86Gy, and the mean number of gamma radiation shots was 12.56±6.95. …”
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Research on rock strength prediction model based on machine learning algorithm by Xiang Ding, Mengyun Dong, Wanqing Shen

“…By selecting different features, the optimal feature combination for predicting rock compressive strength was obtained, and the optimal parameters for different models were obtained through the Sparrow Search Algorithm (SSA). Finally, four regression evaluation indicators, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2), were used to evaluate the predictive performance of the established regression models. …”
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Live Weight Prediction in Norduz Sheep Using Machine Learning Algorithms by Cihan Çakmakçı

“…The results showed that the prediction performance validated using the test dataset indicated that RF had the lowest values of Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percent Error (MAPE). …”
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Stability Conditions for the Leaky LMS Algorithm Based on Control Theory Analysis by Dariusz BISMOR, Marek PAWELCZYK

“…The Least Mean Squares (LMS) algorithm and its variants are currently the most frequently used adaptation algorithms; therefore, it is desirable to understand them thoroughly from both theoretical and practical points of view. …”
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Compression Index Regression of Fine-Grained Soils with Machine Learning Algorithms by Mintae Kim, Muharrem A. Senturk, Liang Li

“…The dataset includes LL, PL, <i>W</i>, PI, <i>G_s</i>, and <i>e</i>₀ as the inputs, with <i>C_c</i> as the output parameter. The algorithms are trained and evaluated using metrics such as the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), and root mean squared error (RMSE). …”
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Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms by Farman Ullah Khan, Faridoon Khan, Parvez Ahmed Shaikh

“…Abstract The study aims at forecasting the return volatility of the cryptocurrencies using several machine learning algorithms, like neural network autoregressive (NNETAR), cubic smoothing spline (CSS), and group method of data handling neural network (GMDH-NN) algorithm. …”
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Correlation Filtering Algorithm of Infrared Spectral Data for Dim Target Tracking by Wenjian Zheng, An Chang, Qi Wang, Jianing Shang, Mandi Cui

“…After the image noise reduction processing by the mean shift filtering algorithm, the infrared small and weak target image data model is constructed by using the denoised infrared small and weak target image. …”
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Predicting algorithm of attC site based on combination optimization strategy by Zhendong Liu, Xi Chen, Dongyan Li, Xinrong Lv, Mengying Qin, Ke Bai, Zhiqiang He, Yurong Yang, Xiaofeng Li, Qionghai Dai

“…The algorithm has better portability and higher prediction accuracy compared with the existing advanced algorithms, among which the Pearson correlation coefficient is 0.87, explained variance score is 0.73, root mean square error is 0.006 and mean absolute error is 0.041. …”
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Homogenization of the Probability Distribution of Climatic Time Series: A Novel Algorithm by Peter Domonkos

“…The input dataset of the algorithm is identical with the homogenization results for section means of the studied time series. …”
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Development of Traditional Algorithm Used in Denoising to Enhance Contrast of the Color Images by Hanan Ali, Esraa Al-Majed, Asmaa Nadhim, Rahma Saleem

“…In this research applied  traditional algorithm filter to improve the <strong>Adaptive Contrast Enhancement</strong> Global  Filter (ACE _mean) and has been the development of this algorithm to a new two Hybrid algorithms to improve the contrast Enhancement (<strong>Median Contrast Enhancement</strong> ACE_median) and the other algorithm is (<strong>Max & Min Contrast Enhancement ACE_max&min</strong>). the two hybrid algorithms obtained from merging two available methods, first is the traditional algorithm (ACE_mean)  with the second methods of another practice in improving the image is (<strong>Smoothing Images Enhancement</strong>) which is used to removing the noise from images .the results of each method were compared with the results of  other algorithms to show the best of them.…”
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Forest Fire Detection Algorithm Based on Improved YOLOv11n by Kangqian Zhou, Shuihai Jiang

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Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

“…To address these challenges, this study proposes a novel framework that combines Transformer models with Metaheuristic Algorithms (MHAs), including the Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to enhance agricultural price forecasting accuracy. …”
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Development of recognition algorithms in the control system of robot drives for plucking tea by Yan Yang, Chicherin I.V., Lijun Zhao, Chanjuan Long, Ignatieva E.A.

“…This study focuses on image recognition of tea Shoots using an object detection algorithm based on a deep learning framework. The developed algorithms are used in the control system of the robot's drives for collecting tea. …”
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Machine Learning Algorithm for Estimating Surface PM2.5 in Thailand by Pawan Gupta, Shanshan Zhan, Vikalp Mishra, Aekkapol Aekakkararungroj, Amanda Markert, Sarawut Paibong, Farrukh Chishtie

“…Abstract We have used NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) reanalysis data of aerosols and meteorology into a machine learning algorithm (MLA) to estimate surface PM2.5 concentration in Thailand. …”
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Adaptive image encryption approach using an enhanced swarm intelligence algorithm by Sachin Minocha, Suvita Rani Sharma, Birmohan Singh, Amir H. Gandomi

“…ICO-HO updates the position of hippopotamuses using ICO and opposition-based learning, which enhances the exploration and exploitation capabilities of the HO algorithm. ICO-HO algorithm’s better performance is signified by the Friedman mean rank test applied to mean values obtained on the CEC-2017 benchmark functions. …”
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Study on the Switching Model Predictive Control Algorithm in Batch Polymerization Process by Jong Nam Kim, Chun Bae Ma, Hyok Jo, Un Chol Han, Hyon-Tae Pak, Son Il Hong, Ri Myong Kim

“…The results show that the proposed control system can significantly improve temperature control performance (overshoot: 0.2%, root mean square error: 0.3) compared to before introduction (overshoot: 1.1%, root mean square error: 1.2ྟC) .…”
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On Solving Hyperbolic Trajectory Using New Predictor-Corrector Quadrature Algorithms by Baghdad Science Journal

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