Search Results - regression ((((line algorithm) OR (based algorithm))) OR (_ 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. …”
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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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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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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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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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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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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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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.

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Prediction of forex trend movement using linear regression line, two-stage of multi-layer perceptron and dynamic time warping algorithms by Tiong, Leslie Ching Ow *, Ngo, David Chek Ling *, Lee, Yunli *

“…This paper aims to investigate the repeated trend patterns as features from historical Forex data, which proposes new combination techniques - Linear Regression Line, two-stage of Multi-Layer Perceptron and Dynamic Time Warping algorithms in order to improve the performance of prediction significantly, thus achieving greater accuracy.…”
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Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms by Tiong, Leslie C.O., Ngo, David C.L., Lee, Yunli

“…Forex prediction has become a challenging task in the Forex market since the late 1970s due to uncertainty movement of exchange rates.In this paper, we utilised linear regression equation to analyse the historical data and discover the trends patterns in Forex.These trends patterns are modeled and learned by Artificial Neural Network algorithm, and Dynamic Time Warping algorithm is used to predict the near future trends.Our experiment result shows a satisfactory result using the proposed approach.…”
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Prediction of Forex trend movement using linear regression line, two-stage of multi-layer perceptron and dynamic time warping algorithms by Leslie, Tiong Ching Ow, David, Chek Ling Ngo, Lee, Yunli

“…This paper aims to investigate the repeated trend patterns as features from historical Forex data, which proposes new combination techniques - Linear Regression Line, two-stage of Multi-Layer Perceptron and Dynamic Time Warping algorithms in order to improve the performance of prediction significantly, thus achiev­ing greater accuracy…”
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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.

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Effort Estimation Model for Function Point Measurement by Koh, Tieng Wei

“…Generally, most of the algorithmic models were generated based on historical projects, and therefore, the same methodology has been applied in this research work. …”
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Extended spatial decision tree algorithm for classifying hotspot occurrence by Sitanggang, Imas Sukaesih

“…For comparison, classifiers for hotspots occurrence were also developed using the non-spatial methods namely the ID3 algorithm and the C4.5 algorithm as well as the logistic regression. …”
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Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI) by Ganasan, Shatiskumar, Norazlianie, Sazali

“…We applied these algorithms on their datasets using its GUI or command-line parameters. …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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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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Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Investigation of cross-entropy-based streamflow forecasting through an efficient interpretable automated search process by Chong K.L., Huang Y.F., Koo C.H., Sherif M., Ahmed A.N., El-Shafie A.

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