scholarly journals Neural Network Programming in Python

2019 ◽  
Vol 8 (6S4) ◽  
pp. 373-377
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Programming Language ◽  
Function Approximation ◽  
Learning Rule ◽  
Network Programming ◽  
Short Introduction ◽  
Python Programming Language ◽  
Python Programming ◽  
Backpropagation Learning

In this paper a basic introduction to neural networks is made. An emphasis is given on a two layer perceptron used extensively for function approximation. The backpropagation learning rule is than briefly introduced. A short introduction into Python programming language is made and a program for the perceptron design is written and discussed in some detail. The “neurolab” library is used for this purpose.

scholarly journals APPLICATION OF NEURAL NETWORKS TO DETERMINE THE COORDINATES OF THE SEAT OF FIRE BY MULTIPOINT ELECTRO-OPTICAL SYSTEM

2021 ◽  
pp. 248-251
Author(s):  
Д.Ф. Пирова ◽  
Б.Э. Забержинский ◽  
А.Г. Золин
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
High Performance ◽  
Network Models ◽  
X Rays ◽  
Neural Network Models ◽  
X Ray ◽  
Python Programming Language ◽  
Python Programming

Статья посвящена исследованию методов проектирования интеллектуальных информационных систем и применение моделей искусственных нейронных сетей для диагностического прогнозирования развития пневмонии посредством анализа рентгеновских снимков. В этой работе основное внимание уделяется классификации пневмонии и туберкулеза - двух основных заболеваний грудной клетки - на основе рентгеновских снимков грудной клетки. Данное исследование проводилось при помощи открытой нейросетевой библиотеки Keras и языка программирования Python. Система дает пользователю заключение о том, болен он или нет, тем самым помогая врачам и медицинскому персоналу принять быстрое и информированное решение о наличии заболевания. Разработанная модель, может определить, является ли рентгеновский снимок нормальным или имеет отклонения, которые могут быть пневмонией с точностью 94,87%. Полученные результаты указывают на высокую эффективность применения нейронных сетей при диагностировании пневмонии по рентгеновским снимкам. This paper is devoted to the study of methods of designing intellectual information systems and neural network models application on diagnostic prediction of pneumonia development by X-ray images analysis. This article focuses on the classification of pneumonia and tuberculosis - the two main chest diseases - based on chest x-rays. This study was carried out using the Keras open neural network library and the Python programming language. System returns user a conclusion whether the patient is ill or not helping medical staff to make a quick and informed decision about the presence of the disease. The developed model can determine is the X-ray image normal or has anomalies that can be pneumonia with accuracy up to 94.87%. The results obtained indicate the high performance of the applying neural networks in the diagnosis of pneumonia by X-ray images.

scholarly journals ENCODING OF CATEGORIAL FEATURES IN NEURAL NETWORKS

2021 ◽  
Vol 2021 (1) ◽  
pp. 3-8
Author(s):  
Denis Barkov ◽  
Svetlana Senotova
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Mathematical Model ◽  
Programming Language ◽  
Data Preparation ◽  
Machine Learn ◽  
Python Programming Language ◽  
Coding Method ◽  
Python Programming

The relevance and areas of application of machine learning are investigated, one of the machine learn-ing algorithms - neural networks, as well as one of the data preparation processes before extracting a mathematical model - the coding of categorical features using the target coding method is consid-ered. Implemented a coding algorithm in the Python programming language

Application of Convolutional Neural Network (CNN) for the Prediction of Spam Mail

2021 ◽  
Vol 28 (1) ◽  
Author(s):  
C.I. Ejiofor ◽  
L.C. Ochei
Keyword(s):  
Neural Network ◽  
Natural Language ◽  
Convolutional Neural Network ◽  
Programming Language ◽  
Financial Cost ◽  
Training Time ◽  
Python Programming Language ◽  
Value Loss ◽  
The Rich ◽  
Python Programming

Spam mail has indeed become a global dilemma due to its coevolutionary nature. It has resulted in the loss of organizational resources, possibly financial cost incurred as well as time spent in addressing spam related issues. This has pushed organizations and researchers to the pinnacle of research with the aim of identifying needed solutions. This research paper explores the rich capabilities of Convolutional Neural Network (CNN) for predicting spam mail taking cognizant natural language capabilities. Spam mail prediction was simulated using a simulator built utilizing python programming language to capture the fundamentals of CNN. The CNN training was actualized using 10 epochs. The 1st epoch offers a training time of 4mins, 39s with a loss of 1.7578, accuracy of 0.3508, value loss of 1.2130 and value accuracy 0f 0.5719 while the 10th epoch presents a training time of 4mins, 6s with a loss of 0.5896, accuracy of 0.7936, value loss of 0.8941 and value accuracy of 0.6986.

scholarly journals Prediksi Nilai Tukar Dollar (USD) ke Rupiah (IDR) menggunakan Artificial Neural Network

2019 ◽  
Vol 2 (1) ◽  
pp. 1-7
Author(s):  
Ahmad Saparudin ◽  
Tiya Maulidina
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Exchange Rates ◽  
Business Strategy ◽  
Training Dataset ◽  
Python Programming Language ◽  
The Future ◽  
Business Forecasting ◽  
Artificial Neural ◽  
Python Programming

Prediction (forecasting) is the activity of predicting events in the future. In terms of business forecasting has many uses, especially for the leadership of the company one of them i.e. to define its business strategy in the future. In this research, carried out the predictions of exchange rates dollar (USD) to Indonesian rupiah (IDR) on 11/03/2019 - 15/03/2019 using artificial neural networks (ANN) with a training dataset from 01/01/2018 - 08/03/2019. Establishment of ANN in the study formed in the Python programming language. Based on the research conducted, a decrease in the price of the exchange rate of USD to IDR on 11/03/2019 – 15/03/2019.

A Python application to generate digital signals

2020 ◽  
Vol 65 (1) ◽  
pp. 96-104
Author(s):  
Tatian-Cristian Mălin
Keyword(s):  
Numerical Simulation ◽  
Programming Language ◽  
Digital Signals ◽  
Python Programming Language ◽  
Python Programming

We introduce in this paper an application developed in the Python programming language that can be used to generate digital signals with known frequencies and amplitudes. These digital signals, since have known parameters, can be used to create benchmarks for test and numerical simulation.

An Open Source Finance System for Stocks Backtesting Trade Strategies

2021 ◽  
Vol 12 (2) ◽  
pp. 52-65
Author(s):  
Eviatar Rosenberg ◽  
Dima Alberg
Keyword(s):  
User Interface ◽  
Open Source ◽  
Programming Language ◽  
Capital Market ◽  
Historical Data ◽  
Trading Strategies ◽  
Market Volatility ◽  
Finance System ◽  
Python Programming Language ◽  
Python Programming

A significant part of pension savings is in the capital market and exposed to market volatility. The COVID-19 pandemic crisis, like the previous crises, damaged the gains achieved in those funds. This paper presents a development of open-source finance system for stocks backtesting trade strategies. The development will be operated by the Python programming language and will implement application user interface. The system will import historical data of stocks from financial web and will produce charts for analysis of the trends in stocks price. Based on technical analysis, it will run trading strategies which will be defined by the user. The system will output the trade orders that should have been executed in retrospect and concluding charts to present the profit and loss that would occur to evaluate the performance of the strategy.

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