智能控制的理论和方法

本文简要地回顾了智能控制的发展过程，讨论了智能控制的几个主要理论与方法，最后对智能控制的发展提出了作者的看法。     

用Promax处理LD22-l“模糊带”地震资料

通过LD22-l构造地震资料目标处理,搞清了“模糊带”,引进交互处理系统是成功的.     

Sirius叠前深度偏移在莺歌海盆地“泥拱模糊带”处理中的应用

在对Sirius叠前深度偏移软件应用开发的基础上,分析讨论了Sirius 2D叠前深度偏移速度模型建立、层析成像及演、叠前深度偏移以及深度聚焦等技术环节的基本原理,并以莺歌海盆地某测线的处理为例,具体分析了Sirius 2D叠前深度偏移处理的流程、主要参数及时效.文中还分析讨论了莺歌海盆地中央“泥拱带”叠前深度偏移处理的地质效果.实践表明,莺歌海盆地广泛发育的与“泥拱模糊带”有关的构造各有其特殊性,只有通过3D叠前深度偏移处理才能从根本上解决“泥拱模糊带”的成像问题.     

多目标模糊全局优化设计方法和软件

分析了优化设计在土木工程中应用不够广泛的原因，由此提出了一个能用于工程设计的多目标模糊全局优化设计方法。介绍了按该方法研制的软件ＭＦＤ的功能和性能，以及一个用该软件分析的拱坝体型设计实例。     

球罐活性缺陷的模糊评定方法

根据国内外有关标准和文献,利用模糊数学中的模糊描述和隶属度等概念,首次采用多级模糊综合评定理论,分层次地把活性缺陷的主要监测信息(即声发射源信息)和专家们的经验考虑在内,建立在用球形贮罐声发射源严重度多级模糊综合评定模型和方法,并编制计算机数据分析和处理程序,使评定结果趋于更合理和可靠.并给出在用球形贮罐声发射源严重度多级模糊综合评定算例,结果表明,该评定方法可以达到定量化的程度,与局部无损复验结果有良好的一致性.     

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。     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

Data mining of resilience indicators

In recent years, the Asia-Pacific region has experienced several financial setbacks, including speculative attacks in 1998 and the SARS outbreak in 2003. Financial stresses of this nature are unanticipated, and not all of the dangers can be predicted by the examination of market information and macroeconomic indicators. The Early Warning System (EWS) that has been adopted by the International Monetary Fund may not be able to predict future financial crises for all possible scenarios, because shocks come in many different forms. To supplement the EWS, this paper proposes a data mining framework to measure the resilience of an economy. The resilience framework does not predict a crisis, but rather assesses the current state of health of an economy and its ability to withstand a financial shock should one occur. The framework is based on a feedback system consisting of two stages. The first stage assigns a resilience score to each economy based on a fuzzy logic scoring scheme that is built on the ambiguous reasoning of experts. The second stage uses the classification tree approach to estimate thresholds for each economic indicator, and examines the quality of the fuzzy score. The result from the second stage is then passed back to the first stage as feedback. The final result is obtained when the feedback system reaches its equilibrium state. The proposed resilience framework is applied to the external-sector and the public-sector economies of several countries to illustrate its applicability.     

运用模糊数学原理估算水利水电工程的成本

为了适应水利水电工程成本快速估价的需要,提出了一种建立在模糊数学基本原理基础上的估价模型,克服了工程量清单计价方法计算繁琐的缺点。通过实例说明了该方法的科学性、合理性及实用性。     

An Interval Fuzzy Multiobjective Watershed Management Model for the Lake Qionghai Watershed, China

Integrated watershed management is required to ensure the reasonable use of resources and reconcile interactions among natural and human systems. In the present study, an interval fuzzy multiobjective programming (IFMOP) method was used to solve an integrated watershed management problem. Based on system analysis, an IFMOP model suitable for a lake watershed system {IFMOPLWS} was developed and applied to the Lake Qionghai watershed in China. Scenario analysis and an interactive approach were used in the solution process. In this manner, various system components were incorporated into one framework for holistic consideration and optimization. Integrality and uncertainty, as well as the multiobjective and dynamic characteristics of the watershed system, were well addressed. Using two scenarios, two planning schemes were generated. Agriculture, tourism, macroeconomics, cropland use, water supply, forest coverage, soil erosion, and water pollution were fully interpreted and compared to identify a preferable planning alternative for local agencies. This study showed that the IFMOPLWS is a powerful tool for integrated watershed management planning and can provide a solid base for sustainable watershed management.