Forecasting Pollution Using Numerical Simulation Implementing Artificial Bee Colony Optimization by Geeta Arora, Harshdeep Kaur, Homan Emadifar, Samaneh Roudgarnejad, Hesam Emadifar

“…Since exponential B-spline involves a parameter, the artificial bee colony optimization algorithm is implemented to find the unknown parameters that result in the minimum error. Among the metaheuristic optimization algorithms, the artificial bee colony (ABC) is one that has received the greatest attention from researchers and has been successfully implemented to solve various problems in engineering and sciences. …”
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The Role of Artificial Intelligence in Predicting the Progression of Intraocular Hypertension to Glaucoma by Nicoleta Anton, Cătălin Lisa, Bogdan Doroftei, Ruxandra Angela Pîrvulescu, Ramona Ileana Barac, Ionuț Iulian Lungu, Camelia Margareta Bogdănici

“…The performance of the neural models was evaluated using several metrics: Mean Squared Error (MSE), Normalized Mean Squared Error (NMSE), correlation coefficient (r²), and percentage error (Ep). …”
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Optimization of process parameters in 3D-nanomaterials printing for enhanced uniformity, quality, and dimensional precision using physics-guided artificial neural network by Anita Ghandehari, Jorge A. Tavares-Negrete, Jerome Rajendran, Qian Yi, Rahim Esfandyarpour

“…Traditional trial-and-error methods often result in significant material waste and time consumption. …”
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Evaluating the performance of artificial intelligence models for temperature downscaling (Study area: Ardabil province) by Mohammad Hossein Jahangir, Seyed Mohammad Ehsan Azimi

“…Introduction: Long and short term weather forecasting have been as two of the most important challenges to water and climate researchers. In order to overcome this challenge, several tools, including atmospheric-ocean general circulation model forecasting scenarios, and downscaling models have been developed and used. …”
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Transfer learning for accelerated failure time model with microarray data by Yan-Bo Pei, Zheng-Yang Yu, Jun-Shan Shen

“…Abstract Background In microarray prognostic studies, researchers aim to identify genes associated with disease progression. …”
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Development of a cryptocurrency price prediction model: leveraging GRU and LSTM for Bitcoin, Litecoin and Ethereum by Ramneet Kaur, Mudita Uppal, Deepali Gupta, Sapna Juneja, Syed Yasser Arafat, Junaid Rashid, Jungeun Kim, Roobaea Alroobaea

“…Four performance metrics are selected to evaluate the prediction accuracy namely mean squared error (MSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean squared error (RMSE) for three cryptocurrencies which demonstrates that GRU model outperforms LSTM. …”
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Aplikasi solidwork untuk rancangan CAD 3D pada mesin 3D printer 2x2x2 meter by Budhy Setiawan, Isa Triyanti, Achmad Walid, Ryan Prasetyo, Virna Umro, Delila Cahya

“…Hasil cetak objek 2D memiliki error ukuran bentuk segitiga 4,62%, bentuk straight slog 7,49%, bentuk oval 5,54%, error sudut sebesar 0% dan error skala objek 0%. …”
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Ten simple rules for working with high resolution remote sensing data by Mahood, Adam L., Joseph, Maxwell B., Spiers, Anna I., Koontz, Michael J., Ilangakoon, Nayani, Solvik, Kylen K., Quarderer, Nathan, McGlinchy, Joe, Scholl, Victoria M., St. Denis, Lise A., Nagy, Chelsea, Braswell, Anna, Rossi, Matthew W., Herwehe, Lauren, Wasser, Leah, Cattau, Megan E., Iglesias, Virginia, Yao, Fangfang, Leyk, Stefan, Balch, Jennifer K.

“…Correct, appropriate and competent use of such data requires skills from remote sensing and the data sciences that are rarely taught together. In practice, many researchers teach themselves how to use high-resolution remote sensing data with ad hoc trial and error processes, often resulting in wasted effort and resources. …”
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BLS-QLSTM: a novel hybrid quantum neural network for stock index forecasting by Liyun Su, Dan Li, Dongyang Qiu

“…Extensive experiments on three real stock indices—CSI 300, SSEC, and CSI 500—demonstrate that the BLS-QLSTM model outperforms traditional LSTM and QLSTM models in six performance evaluation metrics: the root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), coefficient of determination (R2), precision, and accuracy. …”
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High-resolution global modeling of wheat’s water footprint using a machine learning ensemble approach by Murat Emeç, Abdullah Muratoğlu, Muhammed Sungur Demir

“…The model achieved a mean absolute error (MAE) of 108.5 m3/t, mean squared error (MSE) of 239.9 m3/t, and mean absolute percentage error (MAPE) of 1.51, along with a high prediction accuracy evidenced by a test score of 98.49% and an R 2 value of 0.87. …”
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Application of Extra-Trees Regression and Tree-Structured Parzen Estimators Optimization Algorithm to Predict Blast-Induced Mean Fragmentation Size in Open-Pit Mines by Madalitso Mame, Shuai Huang, Chuanqi Li, Jian Zhou

“…Among the evaluated models, the TPE-ET model exhibits the best performance with a coefficient of determination (<i>R</i>²), root mean squared error (RMSE), mean absolute error (MAE), and max error of 0.93, 0.04, 0.03, and 0.25 during the testing phase. …”
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Likelihood‐based photograph identification: Application with photographs of free‐ranging bison by Jerod A. Merkle, Daniel Fortin

“…We tested and identified the false‐rejection error rate using 91 photographs, representing 33 known free‐ranging bison (Bison bison), and 117 simulated data sets with varying numbers of unique individuals, morphological measurements, and photograph error. …”
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Modern Diagnostic Techniques for the Assessment of Ocular Blood Flow in Myopia: Current State of Knowledge by Ewa Grudzińska, Monika Modrzejewska

“…Myopia is the most common refractive error and the subject of interest of various studies assessing ocular blood flow. …”
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Automatic Detection of Motorcycle on the Road using Digital Image Processing by sutikno sutikno, Helmie Arif Wibawa, Ragil Saputra

“…To overcome this problem, several researchers have developed detection system of motorcyclist not wear helmet. …”
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Trajectory Tracking via Backstepping Controller with PID or SMC for Mobile Robots by Sinan Yigit, Aziz Sezgin

“…All results and discussions are comparatively stated at the end of the study with related error figures and evaluations.…”
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The Least Limiting Water Range to Estimate Soil Water Content Using Random Forest Integrated with GIS and Geostatistical Approaches by Orhan Dengiz, Pelin Alaboz

“…The uses of machine learning algorithms are being researched with the new developments in the agricultural field. …”
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Linear mixed effects models under inequality constraints with applications. by Laura Farnan, Anastasia Ivanova, Shyamal D Peddada

“…Constraints arise naturally in many scientific experiments/studies such as in, epidemiology, biology, toxicology, etc. and often researchers ignore such information when analyzing their data and use standard methods such as the analysis of variance (ANOVA). …”
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A Hybrid Approach for Forecasting Occupancy of Building&#x2019;s Multiple Space Types by Iqra Rafiq, Anzar Mahmood, Ubaid Ahmed, Ahsan Raza Khan, Kamran Arshad, Khaled Assaleh, Naeem Iqbal Ratyal, Ahmed Zoha

“…The models&#x2019; performances are evaluated using Root Mean Square Error (RMSE), Mean Square Error (MSE), Mean Absolute Error (MAE), and Normalized Root Mean Square Error (NRMSE). …”
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Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop by Rano Agustino

“…From this problem, researchers are interested in analyzing data relating to film audiences in the cinema. …”
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Quantum Vulnerability Analysis to Guide Robust Quantum Computing System Design by Fang Qi, Kaitlin N. Smith, Travis LeCompte, Nian-feng Tzeng, Xu Yuan, Frederic T. Chong, Lu Peng

“…Direct application of QVA has been provided that helps researchers choose a promising compiling strategy at compile time.…”
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