principal component artificial neural network
ANALYSIS OF CITIES DATA USING PRINCIPAL COMPONENT INPUTS IN AN ARTIFICIAL NEURAL NETWORK
... using Artificial Neural Network (ANN) against Trip Rates of that ...using Principal Component Analysis and then Processed in an Artificial Neural ...with principal ...
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Blood hyperviscosity identification with reflective spectroscopy of tongue tip based on principal component analysis combining artificial neural network
... the input variables of classification model. Less input variables bring the complexity reduction of classification model. ANN is used to build the classification model in this work, which is established on the basis of ...
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Prediction of crude protein content in rice grain with canopy spectral reflectance
... by principal component analysis (PCA) method, and the predicted models were built by multiple linear regressions (MLR), artificial neural network (ANN) and partial least squares ...
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Adaptation of multiple regression analysis to identify effective factors of water losses in water distribution systems
... pipe network affecting non-revenue water (NRW) are being actively carried ...as Artificial Neural Network (ANN) and Principle Component Analysis ...the principal components ...
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Human Activity Recognition in Real-Times Environments using Skeleton Joints
... applying principal component analysis (PCA) to finding the Eigen joints by reducing the noises and redundancy on joint ...techniques Principal Component Analysis (PCA) and Artificial ...
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Title: Evolving Neural Network for Kernel Principal Component Analysis
... , artificial neural networks (ANN ), that tune their parameters without a teacher on the basis of the self-learning paradigm [ 3-5 ], are widely used in solving various problems of Data Mining, Exploratory ...
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Performance Analysis of Face Recognition by Principal Component Analysis and Feed Forward Neural Network
... S.N. Kakarwal, received M.E. and B.E. degree in Computer Science and Engineering. She is currently working toward the Ph.D. degree under guidance of Dr. R.R. Deshmukh at Dr. Babasaheb Ambedkar Marathwada Univeristy, ...
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Application of multi sensor data fusion based on Principal Component Analysis and Artificial Neural Network for machine tool thermal monitoring
... of Principal Component Analysis (PCA) and Artificial Neural Networks (ANN) to fuse this potentially large amount of data from multiple ...
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Modelling of some soil physical quality indicators using hybrid algorithm principal component analysis - artificial neural network
... (2010) created a set of soil quality indicators using physical, chemical and biological indicators, including aggregate stability, bulk density (BD), particle size [r] ...
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An Enhanced Empirical Method on Choosing the Highest Principal Features and the Number of Hidden Neurons in Principal Component Analysis Artificial Neural Network Face Recognition based System
... Human beings have a very good recognition capabilities of faces and complex patterns and nothing can affect this capability. The neurons of the human brain are trained by learning the face of a person and they can ...
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Hybrid neural networks in rainfall-inundation forecasting based on a synthetic potential inundation database
... hybrid neural network (RiHNN) that combines principal component analysis with a feed-forward network to forecast the real-time 1-hour-ahead water depth of inundation at distributed ...
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Feed Forward Artificial Neural Network Model for Air Pollutant Index Prediction in the Southern Region of Peninsular Malaysia
... of principal component analysis (PCA) and artificial neural network (ANN) to pre- dict the air pollutant index (API) within the seven selected Malaysian air monitoring stations in the ...
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Automated Classification of Brain Tumors using Image Pre Processing and Probabilistic Neural Networks
... probabilistic neural network with the computed feature values. Principal component analysis is used for reduction of the dimensionality of the training ...
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A Hybrid Approach for Breast Cancer Classification and Diagnosis
... combining artificial intelligent based learning technique with multivariate statistical ...(Principal Component Analysis) and Artificial Neural Network ...
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Nondestructive identification of tea (Camellia sinensis L ) varieties using FT NIR spectroscopy and pattern recognition
... and Artificial Neural Network (ANN) were compared to construct the identification models based on Principal Component Analysis ...of principal components factors (PCs) was ...
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A Study of Feature Reduction Techniques and Classification for Network Anomaly Detection
... Improved Principal Com- ponent Analysis (IPCA) method was proposed for feature reduction by ...named Principal Component Analysis Neural Network ...
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Analysis of cardiovascular (cvd)/coronary heart diseases(chd) using artificial neural network (ann)
... Experimentally, the neural networks are used to model the human cardiovascular system. By building a model of the cardiovascular system of an individual and then comparing with the real time physiological ...
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Protection and Controlling of Transmission Lines by using Machine Learning Techinique
... The neural system way to deal with issue location may even be uncovering as an example acknowledgment detriment the ANN is prepared to recognize unadulterated snakelike flag as pointers of a standard framework ...
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Text Recognition using Convolutional Neural Network: A Review
... The proposed structured of the survey is a three layer architecture. First is the input layer which receives input from the segmented character images of standard size. Second layer is a hidden layer, this layer is use ...
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ONLINE EMG SIGNAL ANALYSIS FOR DIAGNOSIS OF NEUROMUSCULAR DISEASES BY USING PCA AND PNN
... use principal component analysis ...a principal component, PC, in this case the first principal component, ...first component explaining more of the variation in the ...
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