Search Results - (( pattern machine algorithm ) OR ( patterns warping algorithms ))

Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
Get full text

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 *

“…Thus, this motivates us to investigate possibility of repeated trend patterns from historical Forex data. 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.…”
Get full text
Get full text
Get full text

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

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

“…Thus, this motivates us to investigate possi­bility of repeated trend patterns from historical Forex data. 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…”
Get full text
Get full text

One dimensional image processing for eye tracking using derivative dynamic time warping by Mokhtar, Norrima, Arof, Hamzah, Iwahashi, M.

“…Derivative Dynamic Time Warping (DDTW) is chosen as the classifier for this experiment since it can match patterns from one dimension data sequences with varying length. …”
Get full text
Get full text
Get full text

NN with DTW-FF Coefficients and Pitch Feature for Speaker Recognition by Sudirman, Rubita, Salleh, Sh-Hussain, Salleh, Shaharuddin

“…This paper proposes a new method to extract speech features in a warping path using dynamic programming (DP). The new method presented in this paper described how the LPC feature is extracted and those coefficients are normalized against the template pattern according to the selected average number of frames over the samples collected. …”
Get full text
Get full text

Local DTW coefficients and pitch feature for back-propagation NN digits recognition by Sudirman, R., Salleh, Shahruddin Hussain, Salleh, Sh-Hussain

“…This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. …”
Get full text

An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

“…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. …”
Get full text
Get full text

An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

“…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. …”
Get full text
Get full text

Local DTW Coefficients and Pitch Feature for Back-Propagation NN Digits Recognition by Sudirman, Rubita, Salleh, Sh-Hussain, Salleh, Shaharuddin

“…This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. …”
Get full text
Get full text
Get full text

Robust speech recognition using fusion techniques and adaptive filtering by Syed Mohamed, Syed Abdul Rahman Al-Haddad, Abdul Samad, Salina, Hussain, Aini, Ishak, Khairul Anuar, Noor, Ali O. Abid

“…The study proposes an algorithm for noise cancellation by using recursive least square (RLS) and pattern recognition by using fusion method of Dynamic Time Warping (DTW) and Hidden Markov Model (HMM). …”
Get full text
Get full text
Get full text

Animal voice recognition for identification (ID) detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

“…In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. …”
Get full text
Get full text

Dog voice identification (ID) for detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

“…In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. …”
Get full text
Get full text

Machine learning predictions of stock market pattern using Econophysics approach by Roslan, Nur Nadia Hani, Abdullah, Shahino Mah

“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
Get full text
Get full text

A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Chun T.S., Malek M.A., Ismail A.R.

“…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”

Advanced flood prediction at forest with rainfall data using various machine learning algorithms by M.S., Saravanan, S., Sivashankar, A., Rajesh, Mat Ibrahim, Masrullizam

Get full text
Get full text

Market prices trend forecasting supported by Elliott Wave's theory by Vantuch, T., Zelinka, I., Vasant, P.

“…The combination of ML algorithms and EW pattern detector achieved significantly higher performance compare to the ML algorithms only.…”
Get full text
Get full text

Design of a pattern classification system using extreme learning machine by Sakthivel Thangavelu

Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Support Vector Machines are considered to be excellent patterns classification techniques. …”
Get full text
Get full text
Get full text

Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Support Vector Machines are considered to be excellent patterns classification techniques.The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and may be done experimentally through time consuming human experience.To overcome this difficulty, an approach such as Ant Colony Optimization can tune Support Vector Machine parameters.Ant Colony Optimization originally deals with discrete optimization problems. …”
Get full text
Get full text
Get full text