地震数据油气预测中的属性优化方法

本文简单介绍了智能信息处理中新出现的RoughSet（RS）理论及属性选择方法，从双相介质地震波传播理论角度，探讨了地震数据油气预测属性优化原理，提出了基于RS理论的地震数据油气预测属性优化方法。实际应用表明；本方法速度快、易实现，而且在优选属性、最大程度地减少提取地震属性种数、提高分类正确率等方面，明显优于其它方法。本方法将成为地震数据油气预测的一种有效手段。     

ADS expert

ADS Expert is an integrated system that (a) provides suggestions about suitable optimization algorithms for a particular structural optimization problem, (b) it offers explanations and guide lines, in the form of hypertext, that refer to the optimization strategy, optimizer and one dimensional search method, (c) it produces the required gradients for the objective function and the constraints using symbolic differentiation, (d) establishes a direct linking with ADS routines and (e) it monitors the evolution of the optimization process. The system can be used as an educational tool for structural optimization and as an efficient integrated system for small to medium size optimization problems for which the objective function and the constraints are given in the form of explicit functions of the design variables. The system is a Windows application and runs quite satisfactorily on PCs.     

变结构变参数设计方法及其在机械CAD中的应用

提出了一种新颖的机械结构设计思想－变结构变参数设计方法，并结合实例，阐述了变结构变参数设计的概念、原则、实施措施和意义。由此对Ｉ－ｄｅａｓ软件包进行了二次开发，编制了发动机曲轴专用ＣＡＤ软件程序，并用某型号发动机曲轴进行了验证。     

矩形件排样的一种优化算法

排样问题是一种总体资源分配问题，这里根据矩形件排样的工艺要求，提出了矩形件排样的一种近似算法，将一块板材分成三部分，每部分排一种零件，使得减料方便，提高了劳动生产率。     

Optimization of downhole pump setting depths in liquid-dominated geothermal systems: A case study on the Balcova-Narlidere field,Turkey

Downhole pumps are being used increasingly more often in low-enthalpy geothermal wells. The depth at which these pumps are installed depends on the physical and chemical characteristics of the geothermal fluid, the production flow rate, and the reservoir pressure and permeability. In this study we have investigated the factors affecting pump setting depths in low-temperature, liquid-dominated geothermal systems and defined the relationship between flow rate and pressure drawdown based on multi-rate test results. The methodology proposed was applied to the Balcova-Narlidere geothermal field, Turkey. It was found that the most important parameters for determining the capacity and setting depth of a downhole pump were flow performance, non-condensable gas concentration, and temperature. The implementation of the methodology is illustrated.     

非理想信道下Colpitts混沌电路的自适应同步研究

本文研究了Colpitts混沌电路在非理想信道条件下的自适应同步问题。引入自适应控制器对输入到响应部分（response system）的衰变混沌信号进行预处理，来补偿衰落信道对于同步性能的影响。给出了系统的数学模型，对恒定信道衰变和时变信道衰变两种非理想信道条件下的混沌ColpiRs电路的自适应同步进行了数值仿真研究。仿真结果表明，对于恒定或慢变化的时变信道衰变，自适应控制器可以有效的提高Colpitts电路响应部分和驱动部分（Drive system）的同步性能。     

Ant colony optimization approach to estimate energy demand of Turkey

This paper attempts to shed light on the determinants of energy demand in Turkey. Energy demand model is first proposed using the ant colony optimization (ACO) approach. It is multi-agent systems in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. ACO energy demand estimation (ACOEDE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear and quadratic. Quadratic_ACOEDE provided better-fit solution due to fluctuations of the economic indicators. The ACOEDE model plans the energy demand of Turkey until 2025 according to three scenarios. The relative estimation errors of the ACOEDE model are the lowest when they are compared with the Ministry of Energy and Natural Resources (MENR) projection.     

黑河右岸溢洪洞左导墙优化试验

黑河水利枢纽右岸溢洪洞为缩短引渠左导墙的长度,减少施工开挖量,降低施工难度,减少工程投资,进行优化试验.通过对7种不同的方案对比分析,选择了合适的体型,满足了工程要求.     

模糊规划在炼油厂生产计划优化中的应用

生产计划的编制是炼油化工企业生产经营管理中的一个关键环节，然而由于市场变化的不确定性，使得企业的长远规划制定受到限制，笔者将模糊数学应用于炼厂生产计划的编制，通过模糊规划对炼油企业生产计划进行优化，使编得的生产计划在一定程度上反映市场的变化并使企业的生产效益最优，为企业管理决策者进行长期规划给予指导，给出了实例来说明该方法的可行性。     

Minimum spanning trees made easier via multi-objective optimization

Many real-world problems are multi-objective optimization problems and evolutionary algorithms are quite successful on such problems. Since the task is to compute or approximate the Pareto front, multi-objective optimization problems are considered as more difficult than single-objective problems. One should not forget that the fitness vector with respect to more than one objective contains more information that in principle can direct the search of evolutionary algorithms. Therefore, it is possible that a single-objective problem can be solved more efficiently via a generalized multi-objective model of the problem. That this is indeed the case is proved by investigating the computation of minimum spanning trees.This work was supported by the Deutsche Forschungsgemeinschaft (DFG) as part of the Collaborative Research Center Computational Intelligence (SFB 531) and by the German-Israeli Foundation (GIF) in the project Robustness Aspects of Algorithms.