Clustering Routing for Wireless Sensor Networks

In wireless sensor networks that consist of a large number of low-power sensors.Because the sensor's energy is limited,one of the main design is to obtain long system lifetime.The authors firstly analyse LEACH and LEACH-C clustering routing for wireless sensor networks.Aimming at their shortcoming,they present a new routing LEACH-NEW.This routing uses multi ho Pinstead of one hop.At last,they use NS2 to simulate them.Simulation show results that new routing exhibits noticeably longer system lifetime than rouing LEACH and LEACH-C.     

A Muti-Objective Network Planning Model for Project

Based on the network planning model developed by the author for an overhaul project of a rolling mill production line in a heavy steel plant, an new multiobjective network planning model is proposed in this paper. The formulations of network time parameters are derived. The optimization problem of multiobjective network planning is also discussed. And it has been found out that the fractional single-objctive network is only one of the cases in this model.     

A MULTI -OBJECTIVE FUZZY DECISION -MAKING APPROACH FOR POWER NETWORK PLANNING UNDER UNCERTAINTY

This paper proposes a multi - objective fuzzy decision - making approach for power network planning under uncertainty ,which simutaneously considers not only the least investment cost,the minimum power loss,the maximum reliability,and the least environmental impacts, but also the uncertainty about the future load growth and the capital investment availability. The validity and effectiveness of the proposed approach is verified with numerical examples.     

The Method of Diagnosing Brain-dysfunction Based on Membership Function and BP Neural Network

Membership functions.formed with the characteristic values obtained by applying the continuous reaction time (CRT) theory from controls and heptic encephalopthy and proposedin this paper.whith these membership functions,the CRT data to be diagnosed are calculated in advance,and then discriminated by BP meural network to differentiate patients with or without braindysfunction.The troubles of low accuracy and efficiency,encountered in training BP network withfuzzy samples.scattered data and extended samples,are solved.     

基于SOFM神经网络的核心种质取样算法

介绍了核心种质和自组织特征映射网络的基本概念，使用自组织特征映射网络的自组织特性对种质性状数据进行了聚类，利用聚类的分组结果，提取核心种质，通过对核心种质的各种参数的检验并与完全随机取样和一般的系统聚类的对比。结果表明，SOFM的取样算法，是一种比较有效快捷的算法，可以在实际中加以应用。     

机械结合面切向接触阻尼的神经网络结构化建模

为了使机械结合面切向接触阻尼实验数据便于在机械结构CAD中应用，本文基于人工神经网络的非线性映射能力，提出了机械结合面切向接触阻尼基础数据的神经网络结构化建模方法，并进行了实例建模。结果表明，该方法实用、有效，建模精度和建模效率较高，而且集传统建模与建库思想于一体，实现了多种结合条件下的机械结合面切向接触阻尼基础数据的统一建模。     

移动机器人避障路径规划方法研究

以全自主移动机器人为研究平台，介绍了移动机器人的硬件体系结构、避障行为决策、避障运动控制等。提出一种足球机器人避障路径规划方法，该方法吸取了栅格法信息处理量小的优点，只对障碍物的威胁点进行检测，弥补了其在特征匹配方面的不足，同时无需考虑障碍物的运动状态和运动速度，提高了机器人避障的灵活性和鲁棒性。     

饲喂机器人的研究与开发

精确饲喂的机器人主要由行走机构、料箱、分料螺旋和控制系统等部分组成,利用霍尔传感器和无线识别装置分别实现自身的精确定位以及奶牛的识别。机器人的控制器采用PIC16F877微处理器构成,主要完成机器人的运动控制以及与管理微机的数据交换。饲喂机器人效率高、成本低,定量饲喂有利于提高奶牛的产奶量,适合在奶牛场推广和应用。     

基于多信息融合的疫苗制备中鸡蛋胚体分拣系统

采用多信息融合方法研究疫苗制备中鸡蛋胚体状态的识别与分拣技术。在研究不同状态鸡蛋胚体图像特征、温度衰减和透光度变化情况的基础上,得出活胚图像中血管多、粗且呈放射状,弱胚图像中血管少、细且断裂,死胚图像内部均匀无血管,污染胚图像内部有明显黑块特征;鸡蛋胚体从37.8℃的孵化箱中取出置于25℃室温环境,活胚、弱胚、污染胚、死胚的温度衰减速度依次增大;活胚的透光度随孵化时间增加而逐渐降低,其他胚体透光度变化相对较小。将图像、温度、透光度信息特征融合,建立BP神经网络信息融合模型对鸡蛋胚体状态进行识别。最后,从37.8℃孵化箱中抽取80枚孵化6 d的鸡蛋胚体放置于室温10 min后,采集图像、温度和透光度信息,进行试验验证。结果表明多信息融合系统的识别准确率为96.25%,比单用图像、温度和透光度传感器进行识别的准确率分别提高了6.25%、13.75%和8.75%。