A localization algorithm of weighted maximum likelihood estimation is presented for wireless sensor network based on ZigBee. Location accuracy is sensitive to ranging accuracy which has an inverse relationship with distance between reference node and blind node. Thus weight matrix is introduced to the traditional maximum likelihood estimation method. Theoretical analysis and simulation results ...

The inverse optimization problem is to modify the weight (or cost, length, capacity and so on) such that a given feasible solution becomes an optimal solution. In this paper, we consider the inverse min–max spanning tree problem under the weighted sum-type Hamming distance. For the model considered, we present its combinatorial algorithm that runs in strongly polynomial times. c © 2007 Elsevier...

In many circumstances where multiple agents need to make a joint decision, voting is used to aggregate the agents’ preferences. Each agent’s vote carries a weight, and if the sum of the weights of the agents in favor of some outcome is larger than or equal to a given quota, then this outcome is decided upon. The distribution of weights leads to a certain distribution of power. Several ‘power in...

rainfall erosivity is the ability of rainfall to detach the soil particles. this study was conducted to evaluate spatial variability of rainfall erosivity indices in khouzestan province. the point data of indices (ei30, aim, ke>1 and onchev indices) in 74 stations were used to generate spatial erosivity maps through deterministic and geostatistical interpolation methods (radial basis functions,...

Given an instance of the minimum cost flow problem, the corresponding inverse problem is to modify the arc costs as little as possible so that a given feasible flow becomes optimal to the modified minimum cost flow problem. In this article, we study this inverse problem in that the modifications are measured by the weighted bottleneck-type Hamming distance. We present a new efficient algorithm ...