نتایج جستجو برای: layer perceptron

تعداد نتایج: 288007  

Journal: :تحقیقات جغرافیایی 0
حمیدرضا عزیزی گروه جغرافیا دانشگاه آزاد اسلامی واحد نجف آباد مجید منتظری دانشگاه اصفهان

forecasting of temperature is a very important in meteorology. air temperature prediction is of a concern in environment, industry and agriculture. temperature with precipitation are important factors in meteorology and are used in classification of climate. in this paper we want to predict average monthly temperature for chosen station of isfahan province. an artificial neural network is a pow...

Journal: :International Journal of Multimedia and Ubiquitous Engineering 2017

Journal: :Transaction of the Korean Society of Automotive Engineers 2020

Journal: :International Journal on Smart Sensing and Intelligent Systems 2015

Journal: :International Journal of Modeling, Simulation, and Scientific Computing 2015

Journal: :Frontiers in Energy Research 2023

The existing voltage sag source localization only utilizes one simulation type or measurement data based on sampled waveform data. Moreover, it requires more storage space and transmission channels cannot combine the advantages of simulated data, resulting in poor applicability model. Hence, this paper proposes a locating method transfer learning from information event list combined with grid s...

Journal: :International Journal of Grid and Distributed Computing 2018

2016
Imen Triki

This paper compares, for a microfinance institution, the performance of two individual classification models: Logistic Regression (Logit) and Multi-Layer Perceptron Neural Network (MLP), to evaluate the credit risk problem and discriminate good creditors from bad ones. Credit scoring systems are currently in common use by numerous financial institutions worldwide. However, credit scoring using ...

2014
Madhusudan Roy

A computer aided diagnosis methodology for identifying pathology of human liver using 11 statistical textural features extracted from ultrasonography of 14 fatty and 28 normal livers is presented. It was found that supervised classification could differentiate these two classes of data while unsupervised learning failed to achieve that. For supervised learning input sets were constructed in two...

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