Water resource planning is very important for water resources management. A desirable water resource planning is typically made in order to satisfy multiple objectives as much as possible. Thus the water resource planning problem is actually a Multiple Attribute Decision Making (MADM) problem. The aim of this study is to put forward a new decision method to solve the problem of water resource planning in which attribute values expressed with triangular fuzzy numbers. The new method is an extension of projection method. To avoid the subjective randomness, the coefficient of variation method is used to determine the attribute weights. A practical example is given to illustrate the effectiveness and feasibility of the proposed method.
In this paper, the object recognition module of a visual auxiliary system, InVision, called IR-VP, is presented. (1) Deep multimodal neural network (DMNN) is presented to enhance CNNs' sampling abilitiy and feature resolutions. (2) Deep distance learning (DDL) is presented to find similarity and reduce representation redundancy. (3) The light weight MobileNet is used to accelerate. Extensive experiments demonstrate that the proposed approach significantly outperforms state-of-the-arts.
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