The Evolution of R&D Networks

Solving fractional evolution problem in Colombeau algebra by mean generalized fixed point

‎The present paper is devoted to the existence and uniqueness result of the fractional evolution equation $D^{q}_c u(t)=g(t,u(t))=Au(t)+f(t)$‎ ‎for the real $qin (0,1)$ with the initial value $u(0)=u_{0}intilde{R}$‎, ‎where $tilde{R}$ is the set of all generalized real numbers and $A$ is an operator defined from $mathcal G$ into itself‎. Here the Caputo fractional derivative $D^{q}_c$ is used i...

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation

Optimal Choice of Random Variables in D-ITG Traffic Generating Tool using Evolutionary Algorithms

Impressive development of computer networks has been required precise evaluation of efficiency of these networks for users and especially internet service providers. Considering the extent of these networks, there has been numerous factors affecting their performance and thoroughly investigation of these networks needs evaluation of the effective parameters by using suitable tools. There are se...

The Association Between Inflammatory Biomarkers and Vitamin D Level With Evolution and Severity of Stroke

Background and purpose: Vitamin D deficiency has been shown to be linked to evolution of ischemic stroke, but the data regarding the association between stroke severity and vitamin D level is scarce. Materials and methods: Patients with first-ever acute ischemic stroke in the middle cerebral artery (MCA) territory within 7 days after the stroke were recruited. The control group included age an...

Image Backlight Compensation Using Recurrent Functional Neural Fuzzy Networks Based on Modified Differential Evolution

In this study, an image backlight compensation method using adaptive luminance modification is proposed for efficiently obtaining clear images.The proposed method combines the fuzzy C-means clustering method, a recurrent functional neural fuzzy network (RFNFN), and a modified differential evolution.The proposed RFNFN is based on the two backlight factors that can accurately detect the compensat...

Using Neural Networks with Limited Data to Estimate Manufacturing Cost

Neural networks were used to estimate the cost of jet engine components, specifically shafts and cases. The neural network process was compared with results produced by the current conventional cost estimation software and linear regression methods. Due to the complex nature of the parts and the limited amount of information available, data expansion techniques such as doubling-data and data-cr...