[PDF] Top 20 ANALYSIS OF CITIES DATA USING PRINCIPAL COMPONENT INPUTS IN AN ARTIFICIAL NEURAL NETWORK
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ANALYSIS OF CITIES DATA USING PRINCIPAL COMPONENT INPUTS IN AN ARTIFICIAL NEURAL NETWORK
... study. Data related to these 26 cities regarding various travel parameters and Land –use parameters have been obtained using various sources and ...reduced using Principal ... See full document
11
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 ... See full document
7
Fault diagnostic model for rotating machinery based on principal component analysis and neural network
... In this section, for further validation of the proposed model fuel metering (MF) data parameter is this time selected as the network output. The three collected sensor variables (temperature, pressure and ... See full document
5
Classification of Partial Discharge Measured under Different Levels of Noise Contamination
... discharge data contaminated by noise were ...and principal component analysis (PCA) ...performed using three different artificial intelligence classifiers, which include ... See full document
20
Hybrid neural networks in rainfall-inundation forecasting based on a synthetic potential inundation database
... Artificial neural networks (ANNs) have become an at- tractive inductive approach in hydrological forecasting be- cause of their flexibility and data-driven learning in build- ing models, as well as ... See full document
17
Fuel qualification using quartz sensors
... statistical data analysis including Principal Component Analysis and Neural Network methods, it was possible to conclude that the sensor array is able to distinguish the ... See full document
7
Title: Evolving Neural Network for Kernel Principal Component Analysis
... Today a group of artificial neural networks (ANN), which solve the task of allocating a fixed number m main components such as neural networks of T. Sanger [8] , E. Oja - J. Karhunen [9] , J. Rubner ... See full document
8
A machine learning based fast forward solver for ground penetrating radar with application to full waveform inversion
... and using an innovative training technique for the neural network, that is then used to predict the resulting waveform based on those ...utilizes principal component analysis ... See full document
9
Segmentation of dust storm areas on Mars images using principal component analysis and neural network
... Generally speaking, Martian dust storms are bright in the red band and as dark as the surface in the blue band. On the other hand, Martian clouds are bright in the red and blue bands and especially much brighter than the ... See full document
12
MRI BRAIN IMAGE CLASSIFICATION USING POLYNOMIAL KERNEL PRINCIPAL COMPONENT ANALYSIS WITH NEURAL NETWORK
... techniques. Artificial Neural Networks (ANN) [2] [13], Support Vector Machine (SVM) [6], k- Nearest Neighbor (k-NN) [13] and feed forward back propagation [17] are important supervised techniques and ... See full document
8
Blood hyperviscosity identification with reflective spectroscopy of tongue tip based on principal component analysis combining artificial neural network
... Experiment system consists of computer, light source, spectrometer, and optical fiber. Two Dell computers (CPU: Intel core i5-4210 M, 2.60 GHz; RAM 4.00 GB, 64bit) are used as the processor for spectrometer control and ... See full document
12
Simulation of pornography web sites (PWS) classification using principal component analysis with neural network
... the data are constructed by high similarity web content (such as pornography and sex education web ...by using PCA where the major large input information is maintained while tactically reducing the input ... See full document
13
Face Recognition Using Principal Component Analysis
... Abstract— Face recognition is one of the most relevant applications of image analysis. It’s an efficient task (true challenge) to build an automated system with equal human ability to face recognised. Face is a ... See full document
6
Contribution of Artificial Neural Networks to the Identification and Detection of Targets Concerning Mobility on Remote Sensing Images
... Targets identification on remote sensing images depends essentially on efficiency of the followed classification and analysis methods. In this context, this paper is to present a system for detection and ... See full document
7
Human Activity Recognition in Real-Times Environments using Skeleton Joints
... actions using kinect. A 3D skeleton data is processed from real-time video gesture to sequence of frames and getter skeleton joints (Energy Joints, orientation, rotations of joint angles) from selected ... See full document
9
Modelling of some soil physical quality indicators using hybrid algorithm principal component analysis - artificial neural network
... The influence of some input features on the quality of soil, especially AC, has been considered. For example, Reynolds et al. (2002) showed that AC was affected by clay. FC decreased by the flocculation of clay, which ... See full document
9
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
... extraction using Principal Component Analysis, and recognition using Feed Forward Back Propagation Neural ...when using 80% of the dataset for training, the proposed ... See full document
10
Simulation of Low TDS and Biological Units of Fajr Industrial Wastewater Treatment Plant Using Artificial Neural Network and Principal Component Analysis Hybrid Method
... predicted data of pH, TDS and turbidity, using the best modeling structure, ...available data for modeling, complexity of treatment biological proc- esses, and large changes in the characteristics of ... See full document
7
Adaptation of multiple regression analysis to identify effective factors of water losses in water distribution systems
... estimated using multiple regression analysis, principal compo- nent analysis (PCA), and artificial neural network ...pipe network for predicting the NRW are set as ... See full document
8
Automated Classification of Brain Tumors using Image Pre Processing and Probabilistic Neural Networks
... classification using an amalgamation of image processing techniques and artificial ...probabilistic neural network with the computed feature values. Principal component ... See full document
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