SURFACE AREA CORRECTIONS APPLIED TO A RESOURCE MAP1

ABSTRACT: Generally a difference exists between the horizontal planar area of a watershed as measured on a map and the actual surface area. A technique is presented, utilizing a topographic map, for computing the difference in the two areas as well as yielding a prediction of the actual surface area. Spatial variations in the magnitude of the difference in the two areas for small local sites over the watershed are displayed on computer generated maps. The technique is also used to adjust various inventory variables on maps, such as vegetation density, to reflect actual surface coverage. This allows estimates to be made of the difference in using corrected versus uncorrected area related parameters in mathematical functions describing processes occurring in the atmosphere-surface boundary layer.     

Game theory and hybrid genetic algorithm for energy management and real-time pricing in smart grid: the Tunisian case

ABSTRACT

Microgrids are the key for integrating renewable energy from different sources into smart grid, that is why power grid evolves into a combination of interconnected microgrids. In fact, future power grids are undergoing this groundbreaking change that will help meet the increasing demand of electric power and reduce carbon emission. In this sense we study in this paper, based on measured data, a real case of energy management in the area of Beja located in Tunisia. Indeed, we propose a model for the power exchange which proves the potential of applying game theory in the development of both real-time pricing and energy management mechanism for an open electricity market. We also introduce a hybrid genetic algorithm to compute the Nash Equilibrium. Results show that the proposed smart energy management can decrease the real cost of power up to 20%, to divide the energy transmission losses by a factor of two and to reduce the carbon emission in the area of Beja.     

APPLICATION OF THE GENETIC ALGORITHM FOR OPTIMIZING OPERATION RULES OF THE LiYuTan RESERVOIR IN TAIWAN1

ABSTRACT: A procedure to apply genetic algorithm to optimize operation rules is proposed and applied to the LiYuTan Reservoir in Taiwan. The designed operation rules are operation zones with discount rates of water supply. The first step of the procedure is to predefine the shape of boundary curves of operation zones according to reservoir storage routing. Then, relatively fewer variables are used to describe the curves, and a last genetic algorithm (GA) is applied to optimize the curves. The procedure is applied to the newly built LiYuTan Reservoir for increasing domestic water demands. Shortage index is used to evaluate the performance of operation zones. A year is divided into 36 operational periods, with each month containing three operational periods. The shortage indexes calculated in operational periods are 9.81, 8.27, and 7.13, respectively, for the reservoir without operation rules, applying operation zones optimized by GA with encoding 36 storage levels for each curve, and adopting operation zones optimized by GA with encoding the curves with predefined shape. The average deficits for the three cases are 77.2, 43.6, and 33.3 (10⁴ m³/day), respectively. The results indicate that operation zones optimized by the proposed procedure have smaller shortage indexes and lower average deficits. In addition, the optimized operation zones have less variation and thus are more practical for operation. Conclusively, the proposed procedure utilizing GA to optimize operation zones with predefined shape can provide better and realistic outcomes through limited iterations.     

ANN模型对污水处理系统性能的评价

作者基于B－P算法的人工神经网络，对污水处理系统的性能作了预测和评价，并通过所建立的一个生物转盘处理系统的人工神经网络预测模型实例，验证了人工神经网络用于污水处理系统性能评价方面的可行性与准确性。     

震灾经济损失评估的遗传神经网络模型

地震灾害造成的直接经济损失与很多因素有关:致灾因子强度,主要包括地震震级、发震时间及地点、震源深度和地震动输入参数等;受灾体密度,主要包括衡量城市经济和社会发展水平的人口密度、城市密度、建筑物密度和财产密度等;城市抵抗地震灾害的能力.这里选取震级、地震动输入参数、人均国内生产总值GDP、受灾面积和灾区人口密度作为网络的输入节点,用直接经济损失率作为网络的输出节点,建立了基于遗传神经网络的震灾经济损失评估模型,对地震灾害所造成的经济损失进行评估,实例验证了该方法的有效性.     

OPTIMIZATION OF THE HYDROMETRIC NETWORK OPERATION BY A HEURISTIC TRAVELING SALESMAN ALGORITHM1

ABSTRACT: The problem of determining the optimal route to operate a network of hydrometric gauges within a given area is formulated and solved by an original heuristic traveling salesman algorithm. The algorithm used for solving the problem takes into account the variation of station service time, the eight-hour maximum working day, existence of more than one home base, and the budget constraint. The traveling salesman algorithm is used to solve the optima! assignment problem within a one-day time limit, locating a starting base, stations to visit, and the closest home base. The ending base for the previous day becomes the starting base for the next day, and the assignment procedure is repeated. The computation proceeds from day to day, until all the stations in the considered region are serviced. The solution obtained presents the optimal route to operate a network of hydrometric gauges. The optimization procedure has been applied to the Dauphin hydrometric field area in Manitoba.     

A GENETIC ALGORITHM TO REDUCE STREAM CHANNEL CROSS SECTION DATA1

A genetic algorithm (GA) was used to reduce cross section data for a hypothetical example consisting of 41 data points and for 10 cross sections on the Kootenai River. The number of data points for the Kootenai River cross sections ranged from about 500 to more than 2,500. The GA was applied to reduce the number of data points to a manageable dataset because most models and other software require fewer than 100 data points for management, manipulation, and analysis. Results indicated that the program successfully reduced the data. Fitness values from the genetic algorithm were lower (better) than those in a previous study that used standard procedures of reducing the cross section data. On average, fitnesses were 29 percent lower, and several were about 50 percent lower. Results also showed that cross sections produced by the genetic algorithm were representative of the original section and that near‐optimal results could be obtained in a single run, even for large problems. Other data also can be reduced in a method similar to that for cross section data.     

仿生智能算法在突发环境污染事件应急响应中的应用

近年来随着中国工农业生产和经济建设的快速发展,中国已经进入突发环境事件频发期。然而,中国的突发环境污染事件应急体系仍处于初级应用阶段,不能满足事故频发期事故应对的要求。因此,建立科学的应急决策支持系统具有重大的意义。在决策支持系统中,智能算法处于核心地位。文章对人工智能领域的仿生智能算法在环境应急领域的应用作简要介绍,并明确了多技术集成化应用的研究方向,以期对今后的研究有所启发。     

AutoCAD二次开发技术在声强分布计算与图形表达上的应用

应用AutoCAD二次开发技术,以AutoCAD作为程序的绘图环境,以Visual Basic.NET作为计算环境,针对线屏障和封闭屏障存在的声环境系统,开发了一套计算机程序,以实现声强分布计算和图形表达过程。采用对数加权的处理方法,计算多线屏障的影响;用"线段首尾连接"的方法来追踪等值点。     

基于D优化方法的CSADT设计

考虑到试验设计人员更关注模型参数的估计精度,而传统试验优化方法以产品可靠性与寿命相关参数的预测精度为目标,提出将D优化方法引入恒定应力加速退化试验(CSADT)设计中。首先,用随机过程描述CSADT中产品性能退化的过程,通过对数似然函数,推导Fisher信息矩阵,基于D优化方法建立优化目标,以试验费用为约束条件,明确优化问题,给出最优试验变量:各应力水平、各应力下样本分配和试验时间分配。然后,应用该方法给出仿真实例。最后,通过模型参数偏差的敏感性分析,说明在一定偏差范围内,优化结果具有良好的稳健性。