Integration of surface water with groundwater resources aided by numerical modelling

ABSTRACT

The possibility was studied of a gradual extension of the irrigable area of the Tarlac Irrigation System, located in the alluvial plain of Luzon Island (Philippines). The extension would be made by integrating groundwater with surface water supplied from a reservoir already designed. Aquifer exploitation was studied adopting the criterion that groundwater is a very expensive resource to be turned to only in severe drought years. The objectives of the study were twofold: (a) planning the distribution of the wells (to be drilled during the various stages of the irrigation system development) so as to minimize the pumping cost; (b) establishing a policy for the well management in conjunction with the reservoir operation. Different schemes of the combined system management were analysed on the basis of the climatic and hydrological regime over the period 1950–1972. For this period the monthly water requirements for the different crops and the monthly values of aquifer recharge were computed. The economic analyses were performed using present prices of agricultural products and power together with several different hypotheses about future prices. A finite element model of the semiconfined aquifer was postulated and calibrated; the importance of the return flow from irrigation was also tested. Simulations of exploitation schemes provided a detailed forecast of the aquifer response to the irrigation demands.     

Integration of genetic algorithms and GIS for optimal location search

Optimal location search is frequently required in many urban applications for siting one or more facilities. However, the search may become very complex when it involves multiple sites, various constraints and multiple‐objectives. The exhaustive blind (brute‐force) search with high‐dimensional spatial data is infeasible in solving optimization problems because of a huge combinatorial solution space. Intelligent search algorithms can help to improve the performance of spatial search. This study will demonstrate that genetic algorithms can be used with Geographical Information systems (GIS) to effectively solve the spatial decision problems for optimally sitting n sites of a facility. Detailed population and transportation data from GIS are used to facilitate the calculation of fitness functions. Multiple planning objectives are also incorporated in the GA program. Experiments indicate that the proposed method has much better performance than simulated annealing and GIS neighborhood search methods. The GA method is very convenient in finding the solution with the highest utility value.     

A modified particle swarm optimization algorithm for optimal allocation of earthquake emergency shelters

Allocation for earthquake emergency shelters is a complicated geographic optimization problem because it involves multiple sites, strict constraints, and discrete feasible domain. Huge solution space makes the problem computationally intractable. Traditional brute-force methods can obtain exact optimal solutions. However, it is not sophisticated enough to solve the complex optimization problem with reasonable time especially in high-dimensional solution space. Artificial intelligent algorithms hold the promise of improving the effectiveness of location search. This article proposes a modified particle swarm optimization (PSO) algorithm to deal with the allocation problem of earthquake emergency shelter. A new discrete PSO and the feasibility-based rule are incorporated according to the discrete solution space and strict constraints. In addition, for enhancing search capability, simulated annealing (SA) algorithm is employed to escape from local optima. The modified algorithm has been applied to the allocation of earthquake emergency shelters in the Zhuguang Block of Guangzhou City, China. The experiments have shown that the algorithm can identify the number and locations of emergency shelters. The modified PSO algorithm shows a better performance than other hybrid algorithms presented in the article, and is an effective approach for the allocation problem of earthquake emergency shelters.     

青藏高原小嵩草高寒草甸返青期遥感识别方法筛选

小嵩草高寒草甸是青藏高原的主要植被类型,研究其返青期识别方法对于模拟及预测青藏高原植被物候变化具有重要意义。常用的植被返青期遥感识别方法主要是先对遥感植被指数原始时序数据进行拟合去噪声再求取返青期,各种方法对研究区域、研究经验、参数设置、函数初值设置等有很强的依赖性。为避免返青期识别方法在曲线拟合时对参数初值的依赖性和陷入局部最优解,本文引入了模拟退火算法对双高斯和双逻辑斯蒂函数进行参数优化,并分别对基于以上两种函数及多项式拟合的植被指数时序曲线进行对比,从而选出最佳拟合方法,最后采用最大斜率阈值法、动态阈值法和曲率法识别返青期。利用青藏高原小嵩草高寒草甸34个样本点的返青期地面观测数据及相应的8 km分辨率的NOAA归一化差值植被指数(NDVI)时序数据对以上各种组合的返青期遥感识别方案进行了测试,并选取了153个遥感实验点求取了近30年(1982年—2011年)青藏高原小嵩草高寒草甸的返青期,结果表明:采用双高斯函数拟合的NDVI曲线与原始NDVI时序数据最为接近,在此基础上采用最大斜率阈值法识别的小嵩草高寒草甸返青期及其变化趋势与地面物候观测结果最为一致;同时发现近30年青藏高原小嵩草高寒草甸的平均返青期主要集中在每年的第120—140天,并且呈逐年提前趋势,30年来提前了7天。     

利用引物退火控制技术克隆日本囊对虾性腺差异表达基因

为了解日本囊对虾（Marsupenaeusjaponicus）性腺发育及分化的分子机制,本研究采用改良的引物退火控制技术克隆到了共8个精巢、卵巢的差异表达基因．其中4个为已知基因,分别为凝血酶敏感蛋白基因、皮质棒蛋白基因、增殖细胞核抗原基因和泛素缀合酶基因;4个为未知基因,分别命名为MjACP3-T、MjACP4一T、MjACPl5一T和MjACP4一O基因．采用实时定量PCR方法分析了4个未知基因在性腺发育过程的表达谱,结果表明：MjACP3一T、MjACP4．T和MjACPl5,T基因在日本囊对虾精巢和卵巢中的表达量有显著差异,且在各个时期精巢的表达量均高于卵巢,说明这3个基因可能在精巢的发育中起到某些重要作用．卵巢MjACP4一O基因的表达量变化较大,第5期卵巢的相对表达量达到最高（为1．38）,而其他各个阶段的变化较大,在第4期卵巢的相对表达量最低（为0．03）．在精巢中,MjACP4一O基因的表达量随着精巢逐渐发育成熟呈下降趋势．定量PCR结果与引物退火控制技术的结果有着很好的一致性．研究结果表明,引物退火控制技术是一种简单高效的克隆差异表达基因的技术．采用该技术所克隆到的8个精巢、卵巢的差异表达基因,为进一步了解日本囊对虾性腺发育分化的分子机制提供了基础材料．     

地图自动着色算法研究与实践

从四色问题的抽象模型入手,通过对现有的搜索算法——遗传算法、模拟退火算法这两种算法的原理和流程进行了较为细致的分析,总结出它们在地图四色填充实现过程中的优点与不足之处,并进行比较,找出这两种算法的结合点进行算法的改进优化,将模拟退火算法引入遗传算法,使它们结合起来解决地图四色填充问题,从而形成相对优化的算法,以期达到更...     

Using a hybrid genetic algorithm–simulated annealing algorithm for fuzzy programming of reservoir operation

We present a novel approach for optimizing reservoir operation through fuzzy programming and a hybrid evolution algorithm, i.e. genetic algorithm (GA) with simulated annealing (SA). In the analysis, objectives and constraints of reservoir operation are transformed by fuzzy programming for searching the optimal degree of satisfaction. In the hybrid search procedure, the GA provides a global search and the SA algorithm provides local search. This approach was investigated to search the optimizing operation scheme of Shihmen Reservoir in Taiwan. Monthly inflow data for three years reflecting different hydrological conditions and a consecutive 10‐year period were used. Comparisons were made with the existing M‐5 reservoir operation rules. The results demonstrate that: (1) fuzzy programming could effectively formulate the reservoir operation scheme into degree of satisfaction α among the users and constraints; (2) the hybrid GA‐SA performed much better than the current M‐5 operating rules. Analysis also found the hybrid GA‐SA conducts parallel analyses that increase the probability of finding an optimal solution while reducing computation time for reservoir operation. Copyright © 2007 John Wiley & Sons, Ltd.     

基于退火遗传算法的Fuzzy-PID温控系统

针对温控系统具有大惯性、纯滞后、时变性的特点，设计了一种基于退火遗传算法的Fuzzy-PID控制器，并采用退火遗传算法实现动态优化PID参数。MATLAB仿真结果表明，控制器不失模糊控制鲁棒性强、超调小的特点，且在动态跟踪品质和稳态精度方面明显优于常规的Fuzzy-PID控制。这种PID控制器具有良好的控制性能，体现了退火遗传算法在参数寻优方面所特有的优越性。     

区域特性约束下的油藏物性模拟

为了提高油藏物性模拟的精度,本文提出了包含两个约束条件的目标函数,考虑在既满足井条件与空间结构变化,同时又满足油田范围内观测到的油藏物理性质的约束下,应用模拟退火算法,对孔隙度的空间分布进行预测模拟.由于目标函数有效地结合了静、动态信息,从而降低了模拟结果的不确定性,提高了模型的精度.合成数据的油藏物性模拟试验表明,该方法收敛快、稳定性好,模拟的结果令人满意.