The greenhouse climate is a non-linear system that contains multiple inputs (predictors) and outputs (responses). This project aimed to provide solution, aided by artificial intelligence, the issue of variations in time, input output factors internal can adversely affect tomato seedlings. Machine learning Methodologies such as fuzzy inference neural networks have been applied mimic idealistic b...

Abstract Machine learning algorithms can study existing data to perform specific tasks. One of the well-known machine is backpropagation algorithm, but this algorithm often provides poor convergence speed in training process and a long time. The purpose optimize standard using Beale-Powell conjugate gradient so that time needed achieve not too long, which later be used as reference information ...

This paper presents a new identification technique combining the advantages of artificial neural network (ANN) and genetic algorithm (GA). In order to provide a neural network topology that can be merged into the GA identification technique developed by the author, the time history of the ground acceleration and the system parameters of a variety of SDOF systems are used as the input data of ne...

Pathway reconstruction, which remains a primary goal for many investigations, requires accurate inference of gene interactions and causality. Non-coding RNA (ncRNA) is studied because it has significant regulatory role in plant animal life activities, but interacting micro-RNA (miRNA) long non-coding (lncRNA) are more important. Their not only aid the in-depth research genes’ biological roles, ...

Traditionally, music was considered an analog signal that had to be made by hand. In recent decades, has been highlighted technology can autonomously compose a suite of without any human interaction. To achieve this goal, article suggests autonomous composition technique based on long short-term memory recurrent neural networks. Firstly, the collection is split into sequences unit time, and Mei...