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

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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.…”
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

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). …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

Time-series prediction of sea level change in the east coast of Peninsular Malaysia from the supervised learning approach by Lai V., Malek M.A., Abdullah S., Latif S.D., Ahmed A.N.

Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…The prediction was followed by data preprocessing and feature selection. Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”

Narx network based data-driven algorithm for detection of tray faults in nonlinear dynamic distillation column by Taqvi, S.A.A., Zabiri, H., Tufa, L.D., Uddin, F., Fatima, S.A., Maulud, A.S.

Get full text
Get full text

Predict The Thyroid Abnormality Particular Disease Likelihood of The Symptoms’ Certainty Factor Value and Its Confidence Level: A Regression Model Analysis by Rosyid Ridlo, Al Hakim, Yanuar Zulardiansyah, Arief, Agung, Pangestu, Hexa Apriliana, Hidayah, Aditia Putra, Hamid, Aviasenna, Andriand, Nur Fauzi, Sulaiman, Machnun, Arif, Majmmoud Hussein, A. Alrahman

“…The traditional expert system (TES) in the medical field commonly uses a certainty factor (CF) rule-based algorithm that can be calculated several symptoms to determine the inference solutions. …”
Get full text
Get full text
Get full text
Get full text