[PDF] Top 20 Diseño de vivienda de interés social sustentable
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A Hybrid Model to Forecast Stock Trend Using Support Vector Machine and Neural Networks
... separated using linear SVM, we can use conversion function φ to convert the original 2-dimensional data into a new high-dimensional feature space for linear separable ...classification using what is called ... See full document
570
Machine Learning Perspectives for Dental Imaging
... segmentation using covariance, distance measure are comes under the category of stochastic methodology ...The hybrid methodology is the combination of both structural and stochastic approaches ...of ... See full document
9
Predicting the daily return direction of the stock market using hybrid machine learning algorithms
... with machine learning algorithms are playing an increasingly important role in various application fields, including stock market ...daily stock market returns, especially when using powerful ... See full document
5
Support Vector Machine and Least Square Support Vector Machine Stock Forecasting Models
... to forecast the actual daily close value of Hong Kong Hang Sang Index (HSI) given the past 5-year ...Kong Stock market is not efficient and lack of volume like the US stock market to support ... See full document
18
Determination of Corrosion Types from Electrochemical Noise by Artificial Neural Networks
... Artificial neural network is a new approach to differentiate corrosion ...of forecast, fitting, pattern recognition, few people apply it to the research of electrochemical ...of using one parameter ... See full document
25
Rainfall Prediction using Neural Net based Frequency Analysis Approach
... prediction model based on back propagation neural network for 14 districts of Kerala and also for Kerala as a whole ...district forecast is ...ARIMA model is 145.14 and 262.57 respectively. ... See full document
114
A Fuzzy Based Classification – An Experimental Analysis
... Fuzzy Neural Network and Fuzzy SVM technique for classification of cardiotocographic data set helping patients to predict and reliable diagnosis at the ...Fuzzy Neural Network has been used for ... See full document
24
Automated Vehicle Security System using Convolutional Neural Networks and Support Vector Machine
... selection, model selection, training and validation, testing and evaluation of performance of model and tuning of ...information using Deep Learning ...this model emphases on detection of ... See full document
31
ON MODELING TRACES IN A COMPUTING ENVIRONMENT FOR HUMAN LEARNING BASED INDICATORS
... A prototype Intelligent Heart Disease Prediction System (IHDPS) based on data mining techniques is proposed by Sellappan Palaniappan et al. [5]. The techniques used are Decision Trees, Naˆive Bayes and Neural ... See full document
5
Classification of Partial Discharge Measured under Different Levels of Noise Contamination
... performed using three different artificial intelligence classifiers, which include Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector ... See full document
11
Soft Computing Approaches for Human Action Recognition: A Review
... The support vector machine [SVM] is a training ...called support vector treat as parameter. SVM is based on the machine learning algorithm invented by vapnik in ... See full document
33
A Meta-Stacked Software Bug Prognosticator Classifier
... that neural-net and dynamics-based techniques are less mature than the other classes of techniques and are challenged by the rapid changes in software ...to support the project planning and control ... See full document
8
Technical Methods and Algorithms for Developing Efficient Optical Character Recognition System: An Overview
... A decision tree is a technique that has multilevel decision making process which instead of using the whole features completely to make a choice; different subsets of features are used at different stages of the ... See full document
69
Machine Learning and Artificial Neural Network Process – Viability and Implications in Stock Market Prediction
... Indian stock market and an Indian stock market is a place where every type of investors – small and large – try to maximize their returns by understanding the price ...Artificial Neural Network ... See full document
79
Ecg Signal based Arrhythmia Detection System using Optimized Hybrid Classifier
... the hybrid classifier (SVM and ...used using an optimal objective ...proposed hybrid classifier with ANN. The computation has been performed using performance parameters like Precision, ... See full document
49
Software Susceptibility Forecast Using Attribute Subset Collection and Support Vector Machine
... An evaluation function (also called objective function or scoring function) is needed to distinguish good classifiers from bad ones. The evaluation function used internally by the algorithm may differ from the external ... See full document
29
Experimental Investigation of Classification Algorithms for Predicting Lesion Type on Breast DCE MR Images
... artificial neural network, support vector machine and artificial bee colony optimization algorithm trained neural network are being developed for classification of the suspicious ... See full document
149
Machine learning CICY threefolds
... from Neural Networks and Support Vector Machines (SVM) are used to investigate geometric properties of Complete Intersection Calabi–Yau (CICY) threefolds, a class of manifolds that facilitate ... See full document
51
Online Full Text
... methods, support vector machines (SVMs) are well-known [6] by its highly accurate computational capabilities and high-dimensional data ...By using learning algorithms for classification, they are ... See full document
76
Classification Techniques for Predicting Graduate Employability
... Tree, Support Vector Machines and Artificial Neural Networks are used and being compared for the best ...the model is small which is ... See full document
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