Core periphery valued models in input‐output field: A scope from network theory

Abstract

The use of network theory in the input-output field supposes an interesting alternative that allows structural complexity, weakness and strength to be shown. To this end, we analyse the relative position of each industry via core-periphery models to offer an approach to fundamental economy structure. These models are very flexible and can be applied on Boolean or valued graphs. In order to overcome the usual criticisms, we extend previous works and develop core-periphery valued models. This novel proposal is applied to the analysis of the European and Spanish economies in 1995. JEL classification: C67

Bayesian Optimization RSSI and Indoor location Algorithm of Iterative Least Square

“…After obtaining the distance d , a equation is successfully established and the location of target node (unkown node) can be calculated using least square method [14]. In two dimensional plane, at leas 3 anchors are needed before calculate the location of mere one unknown node (target node).…”

“…According to reference [14], a simplified log-normal distribution model is adopted to describe the relation between distance and RSSS value, which is shown in equation (2).…”

“…Firstly define the target state for the event, which can be seen in equation (14). at t time can be established through processes of forecast and upgradation respectively.…”

ACO and SVM Selection Feature Weighting of Network Intrusion Detection Method

“…  (14) where, F(s opt ) is the fitness function for optimal feature subset in this round. The impact of ρ on the convergence of ant colony optimization algorithm is very obvious.…”

“…Through mapping can solve learning problems of high-dimensional space, with good generalization ability to overcome local minimum, the curse of dimensionality and other issues. It becomes the major network detection algorithm [14][15]. The traditional SVM algorithm assumes that all network intrusion feature have the same importance.…”