Search Results - ((linear algorithm) OR (((((learning algorithm) OR (based algorithm))) OR (learning algorithms))))

Tree-based machine learning in classifying reverse migration/ Azreen Anuar, Nur Huzeima Mohd Hussain and Hugh Byrd by Anuar, Azreen, Mohd Hussain, Nur Huzeima, Byrd, Hugh

“…The findings revealed that tree-based machine learning algorithms performed slightly better than linear-based algorithms in terms of accuracy of prediction, with an improvement of approximately 1%. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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Prediction of earnings manipulation on Malaysian listed firms: A comparison between linear and tree-based machine learning by Rahman, R.A., Masrom, S., Zakaria, N.B., Nurdin, E., Abd Rahman, A.S.

“…Thus, the aim of the paper is to compare the earnings manipulation prediction models developed by using two types of machine learning algorithms; linear and tree categories. The linear based machine learning are Logistic Regression and Generalized Linear Model while the tree based are Decision Tree and Random Forest. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…There exist several types of classification algorithms, and these are based on various bases. The classification performance varies based on the dataset velocity and the algorithm selection. …”
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Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster by Afan H.A., Yafouz A., Birima A.H., Ahmed A.N., Kisi O., Chaplot B., El-Shafie A.

“…algorithm; flooding; forecasting method; machine learning; river flow; sampling; streamflow; Tigris River…”

Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia by Ahmad, M.T., Qaiyum, S., Alamri, A., Islam, S.

“…In this study we have applied several machine learning algorithms to analyse time-series data related to COVID-19 in Saudi Arabia. …”
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Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia by Ahmad, M.T., Qaiyum, S., Alamri, A., Islam, S.

“…In this study we have applied several machine learning algorithms to analyse time-series data related to COVID-19 in Saudi Arabia. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Adaptive beamforming algorithm based on Simulated Kalman Filter by Kelvin Lazarus, Lazarus

“…Zakwan, applies Opposition-Based Learning method to improve the exploration capabilities of SKF algorithm. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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Comparative analysis on the deployment of machine learning algorithms in the distributed brillouin optical time domain analysis (BOTDA) fiber sensor by Nordin N.D., Zan M.S.D., Abdullah F.

“…The algorithms analyzed were generalized linear model (GLM), deep learning (DL), random forest (RF), gradient boosted trees (GBT), and support vector machine (SVM). …”

SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

“…The experiment involved five (5) common algorithms: Linear Regressor, Decision Tree Regressor, Random Forest Regressor, Ridge Regressor and Lasso Regressor. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…The proposed algorithms have been tested on a variety of datasets from the UCI machine learning repository. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…Linear discriminant analysis (LDA) is a very popular method for dimensionality reduction in machine learning. …”
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