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A high-performance neural network algorithm using a Legendre ensemble-based extreme learning machine for solving fractional partial differential equations by Isah, Ibrahim Onimisi, Senu, Norazak, Ahmadian, Ali

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ExtraImpute: a novel machine learning method for missing data imputation by Alabadla, Mustafa, Sidi, Fatimah, Ishak, Iskandar, Ibrahim, Hamidah, Affendey, Lilly Suriani, Hamdan, Hazlina

“…To evaluate the efficiency of our algorithm, several experiments are conducted on five different benchmark healthcare datasets and compared to other commonly used imputation methods, viz. missForest, KNNImpute, Multivariate Imputation by Chained Equations (MICE), and SoftImpute. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…Furthermore, the efficacy of different models based on heuristic hyperparameter tuning is evaluated in which the different kernel function for Support Vector Machine, various distance metrics of k-Nearest Neighbors. The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Enhancing the Yolov8 algorithm for real-time dental segmentation by Mohammed Abed Al Zobaie, Dhiaa

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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. Monte-Carlo simulation is performed by propagating uncertainty to investigate the dominant parameters affecting simulated results. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar by Ahlad, Kumar

“…These feature vectors along with ELM are used in estimating the blur parameters. …”
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State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review by How D.N.T., Hannan M.A., Hossain Lipu M.S., Ker P.J.

Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

“…To find optimum variables, Machine Learning approach needs to be utilized. In this research, an imputation approach using Extremely Randomized Trees (Extra Trees) of ensemble machine learning methods named (ImputeX) is proposed. …”
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Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

“…Although the FMM has many important features with the ability to provide online learning process and can handle the forgetting problem, it suffers from a number of limitations, especially in its learning process i.e., expansion process, overlapping test process, and contraction process. …”
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Intelligent imputation method for mix data-type missing values to improve data quality by Alabadla, Mustafa R. A.

“…To find optimum variables, Machine Learning approach needs to be utilized. In this research, an imputation approach using Extremely Randomized Trees (Extra Trees) of ensemble machine learning methods named (ImputeX) is proposed. …”
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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems by Manap, Zahariah

“…The channel parameters such as received power, time of arrival, and angle of arrival are used as fingerprint features that act as predictors in both learning sessions. …”
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