Approximation ability is of much importance for neural networks. The broad learning system
(BLS)(Chen and Liu, 2018), widely used in the industry with good performance, has been …

This paper expatiates the stability and bifurcation for a fractional-order neural network
(FONN) with double leakage delays. Firstly, the characteristic equation of the developed …

In Indian economy, Agriculture is considered as a one of the strongest pillars. Agriculture
sector contributes significantly in GDP of the country and it provides employability to many …

Sažetak The support rendered by artificial intelligence in plant disease diagnosis and with
drastic progression in the agricultural technology, it is necessary to do pertinent research for …

In this paper, neural network method is first proposed to solve the fractional-order partial
differential equations. The neural network based on the sine and the cosine functions is …

Hopfield neural network (HNN) is considered as an artificial model derived from the brain
structures and it is an important model that admits an adequate performance in …

This paper present novel parallel computing algorithms for numerical solution of nonlinear
fractional-order (FO) models of nuclear reactor. These FO models arise by virtue of …

This article investigates the asymptotical stability of the equilibrium point for a class of
fractional neutral-type delayed neural networks with reaction-diffusion terms in sense of …

The objective of this work is the analysis of subdiffusive processes in BWR reactors. Nuclear
reactors are highly heterogeneous systems where the phenomena at the reactor scale are …

Energy-structure transformation and CO 2-emission reduction are becoming particularly
urgent for China and many other countries. Development of effective methods that are …