Search Results - regression ((((line algorithm) OR (acs algorithm))) OR (((bat algorithm) OR (based algorithm))))

The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”

Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

“…SVR however is inferior in accuracy and thus this paper discusses the usage of an optimized SVR with Evolved Bat Algorithm (EBA) to handle the missing value accurately with high execution time. …”
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Sales prediction for media platforms advertising expenditure using Linear Regression / Nur Athirah Abdurahman by Abdurahman, Nur Athirah

“…The study focuses on the application of the Linear Regression algorithm to predict sales outcomes based on advertising spending patterns. …”
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Depth Map Estimation based on Linear Regression using Image Focus by Malik , Aamir Saeed, Song, Taek Lyul, Choi, Tae-Sun

“…Then linear regression model is used to find lines that approximate these datasets. …”
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DISSERTATION TITLE: AN OPTIMIZED SUPPORT VECTOR REGRESSION USING EVOLVED BAT ALGORITHM FOR HANDLING MISSING VALUES IN DATASETS

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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Abdullah F., Ahmad W.S.H.M.W.

“…The ML-based routing algorithm is compared to the conventional routing algorithm, Routing Information Protocol version 2 (RIPv2). …”

Three-term conjugate gradient method under Armijo line search for unemployment rate in Malaysia / Muhammad Fiqhi Zulkifli by Zulkifli, Muhammad Fiqhi

“…TTDY is the most effective method based on numerical results but only TTRMIL+ can be applied in regression analysis.…”
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Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

“…REFERENCES Agullo, J. (2000). New Algorithms for Computing the Least Trimmed Squares Regression Estimator. …”
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Real time long range (LoRa) based indoor positioning system using Deep Gaussian Process (DGP) algorithm / Ng Tarng Jian by Ng, Tarng Jian

“…This thesis explores the development of a real-time LoRa-based indoor positioning system in industrial production lines. …”
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An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.] by Rastogi, Sarthak, Shrotriya, Archit, Singh, Mitul Kumar, Potukuchi, Raghu Vamsi

“…To this end, this paper studies the classification analysis of intrusion detection using various supervised learning algorithms such as SVM, Naive Bayes, KNN, Random Forest, Logistic Regression and Decision tree on the NSL-KDD dataset. …”
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Twisted pair cable fault diagnosis via random forest machine learning by Ghazali, N. B., Seman, F. C., Isa, K., Ramli, K. N., Z. Abidin, Z., Mustam, S. M., Haek, Haek, Z. Abidin, A. N., Asrokin, A.

“…Then, the random forests algorithms (RFs), a data-driven method, are adopted to train the fault diagnosis classifier and regression algorithm with the processed fault data. …”
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AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION by LAW, JIN MING

“…An algorithm with DenseNet-201 backbone consisting of two branches which are class label classification and bounding box regression is developed. …”
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Two steps hybrid calibration algorithm of support vector regression and K-nearest neighbors by Hamed, Y., Ibrahim Alzahrani, A., Shafie, A., Mustaffa, Z., Che Ismail, M., Kok Eng, K.

“…This paper presents a new hybrid calibration model that is based on two steps K nearest neighbor interpolation and support vector regression. …”
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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

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Poverty risk prediction based on socioeconomic factors using machine learning approach by Mohd Zawari, Nur Farhana Adibah

“…The findings indicated that the Logistic Regression outperformed the other algorithm with 99.06% using cross-validation and 98.42% using the splitting method, and with the best value of precision, recall, and F1-score. …”
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Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions by Shamshad, H., Ullah, F., Ullah, A., Kebande, V.R., Ullah, S., Al-Dhaqm, A.

“…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network by Dahlan N.Y., Kasuan N., Ahmad A.S.

“…This paper estimates leakage current level by modeling it as a function of various meteorological parameters using Hybrid Multilayered Perceptron Networks (HMLP) with Modified Recursive Prediction Error (MRPE) learning algorithms. The results are also compared with the regression analysis done previously. …”

Do CEO and chairman characteristics affect green innovation? evidence from a comparative analysis of machine learning models by Xue, Ruixiang, Ong, Tze San, Demir, Ezgi

“…Using the extreme gradient boosting (XGBoost) algorithm, which is at the forefront of machine learning algorithms, this study comprehensively examines the impact of CEO and chairman characteristics on corporate green innovation. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

“…Feature selection methods such as Boruta, Random Forest (RF), Elastic Net (EN), Recursive Feature Elimination (RFE), learning vector quantization (LVQ), Genetic Algorithm (GA), Cluster Dendrogram (CD), Support Vector Machine (SVM) and Logistic Regression (LR) were combined with RF, SVM, LR, and EN classifiers for 30-day mortality prediction. …”
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