位移反分析的PSA-ANFIS方法研究

地下工程中,通常采用位移反分析方法来确定围岩的力学参数,而现有的位移反分析方法均存在诸多不足之处,为此,采用模式搜索算法、自适应神经模糊推理系统以及正交试验设计方法,建立了位移反分析的PSA-ANFIS方法;同时还对一标准弹塑性问题进行了解析计算,得到了相应的训练数据对、检测数据对和预测数据对;最后采用此方法对该弹塑性问题的力学参数进行了反演。反演结果表明,所建立的位移反分析的PSA-ANFIS方法除了能够充分发挥ANFIS的各种优点外,还能有效地减少模型建立和参数调节过程中的人为干预,因此是一种优异的位移反分析方法。     

基于自由搜索的投影寻踪水质综合评价方法

为解决水质评价指标的不相容性以及现有评价方法对等级的分辨率较粗略等问题,提出了水质状况评价的投影寻踪方法(Projection Pursuit,PP).根据地表水环境等级划分标准,构建了能够反映水质状况变异信息的投影指标函数;引入自由搜索(Free Search,FS)算法,优化投影指标函数寻求最佳投影方向;利用最佳投影方向信息研究了各种水质指标对水质状况评价的影响程度.以山西省汾河流域为例,进行水质评价分析,并与基于加速遗传算法优化投影寻踪模型(RAGAPP)和利用粒子群优化投影寻踪模型(PSOPP)得到的投影值结果进行对比.实例应用表明,该模型评估结果误差精度优于RAGAPP和PSOPP,评价结果符合当地水质状况实际情况,且对水质等级划分清晰.     

救援机器人的发展及其在灾害救援中的应用

灾害搜救工作的复杂性、危险性和紧迫性给救援工作带来了极大的困难。救援机器人以其体积小、灵活等诸多优点成为灾害辅助救援的有效工具并引起全世界的广泛关注。文中分析了救援行动中使用救援机器人的必要性和可行性,介绍了国内外救援机器人的研究历史和发展概况,对目前的几种救援机器人运动方式和通讯控制方式的优缺点进行了比较。通过分析灾害救援行动中救援机器人所面临的挑战以及国内外救援机器人技术研究的热点及发展方向,给我国研制开发救援机器人提出了若干建议。     

A beetle antennae search improved BP neural network model for predicting multi-factor-based gas explosion pressures

A gas explosion in an underground structure may cause serious damage to the human body and ground buildings and may result in huge economic losses. The pressure of the gas explosion is an important parameter in determining its severity and designating an emergency plan. However, existing empirical and computational fluid dynamics (CFD) methods for pressure prediction are either inaccurate or inefficient when considering multiple influencing factors and their interrelationships. Therefore, for a more efficient and reliable prediction, the present study developed a multifactorial prediction model based on a beetle antennae search (BAS) algorithm improved back propagation (BP) neural network. A total of 317 sets of data which considered factors of geometry, gas, obstacle, vent, and ignition were collected from previous studies. The results showed that the established model can predict pressures accurately by low RMSE (43.4542 and 50.7176) and MAPE (3.9666% and 4.9605%) values and high R² (0.7696 and 0.7388) values for training and testing datasets, respectively. Meanwhile, the BAS algorithm was applied to improve both the calculation efficiency and the accuracy of the proposed model by enabling a more intelligent hyperparameter tuning method. Furthermore, the permutation importance of input variables was investigated, and the length (L) and the ratio of length and diameter (L/D) of geometry were found to be the most critical factors that affect the explosion pressure level.     

1种机器人工作区域协同搜索避障巡检策略

为解决工作区域搜索待操作目标的不确定性以及单一策略无法解决障碍物区域多搜索目标遍历与避障的问题,提出1种随机与固定搜索相结合的协同巡检策略。该策略在重点监测点通过引入非线性收敛因子及动态权重策略的改进灰狼优化算法遍历多任务点进行固定路线搜索;在非重点监测区域为差速转向移动机器人赋予三视野扫描线,并运用其灵活转动的特点进行随机路线搜索;通过交互式人工标记的方法定位搜索目标点并对其进行标记,运用改进灰狼优化算法对标记出的多目标点进行遍历顺序规划及D*算法避障到达;通过5个国际通用工程函数仿真测试改进的灰狼优化算法。结果表明:改进的灰狼优化算法能加快收敛速度,增强模型的求解精度,加强算法的稳定性,同时验证随机与固定相结合的区域协同搜索避障巡检策略的有效性。     

Science guides search and rescue after the 2006 Philippine landslide

A rockslide-debris avalanche destroyed the remote village of Guinsaugon in Southern Leyte, Philippines, on 17 February 2006. Although search and rescue procedures were implemented immediately, the scale of the landslide and a lack of information about its nature resulted in unfocused and imprecise efforts in the early days of the operation. Technical support was only introduced five days after the event, provided by a team of volunteer geologists, geophysicists, and meteorologists. By the time search and rescue operations were transferred to specific target sites, however, the chances of finding survivors trapped under the rubble had diminished. In such critical situations, speed, accuracy, and the maximum appropriation of resources are crucial. We emphasise here the need for a systematic and technically informed approach to search and rescue missions in large-scale landslide disaster contexts, and the formulation of better disaster management policies in general. Standard procedures must be developed and enforced to improve how civil authorities respond to natural calamities.     

基于最优搜索理论的流域事故污染源搜索新方法

通过对时间资源有限情况下的流域事故性污染源最优搜索策略的研究,从搜索目标状态和搜索资源能力两个方面分析了影响流域事故性污染源最优搜索的因素,根据最优搜索理论,构建了流域事故性污染源最优搜索模型体系,在确定了目标初始概率分布、探测函数形式和时间资源上限以后,即可计算出最优的搜索资源分配。     

基于网络搜索行为的公众环境关心指标体系构建研究

利用环境相关的网络搜索数据构建指标体系,对中国公众环境关心程度进行评价.构建的环境关心指标体系包括环境污染关心、环境知识关心、环境法规关心和环境行为关心4分类指数和42具体指标.分析结果表明,环境关心指数主要受节能、减排、绿色出行等环境行为关心类指标影响;2011年以来,中国公众环境关心指数取值集中在100~200之间,且呈稳步上升趋势,并具有明显的季节性变动特征.     

互联网与环境科学技术

互联网的普及对推动环境科学技术发展起着很大作用 ,一方面 ,合理利用网络的资源可以使科研工作事半功倍 ;另一方面 ,互联网逐渐成为环境技术的推广应用、环保设备产品宣传和销售中的重要环节。本文介绍与环境科学技术相关的网络资源 ,包括文献检索、软件和环境科学讨论组、数据库、环保技术设备信息平台等     

A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems

Hybrid renewable energy systems (HRES) turned into an appealing choice for supplying loads in remote areas. The application of smart grid principals in HRES provides a communication between the load and generation from the HRES. Using smart grid in the HRES will optimally utilize the generating resources to reschedule the loads depending on its importance. This paper presents a new proposed design and optimization simulation program for techno-economic sizing of grid-independent hybrid PV/wind/diesel/battery energy system using Cuckoo search (CS) optimization algorithm. Using of CS will help to get the global minimum cost condition and prevent the simulation to be stuck around local minimum. A new proposed simulation program (NPSP) is acquainted using CS to determine the optimum size of each component of the HRES for the lowest cost of generated energy and the lowest value of dummy energy, at highest reliability. A detailed economic methodology to obtain the price of the generated energy has been introduced. Results showed that using CS reduced the time required to obtain the optimal size with higher accuracy than other techniques used iterative techniques, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Numerous significant outcomes can be extracted from the proposed program that could help scientists and decision makers.