A New Approach to Abstract Syntax with Variable Binding

The permutation model of set theory with atoms (FM-sets), devised by Fraenkel and Mostowski in the 1930s, supports notions of ‘name-abstraction’ and ‘fresh name’ that provide a new way to represent, compute with, and reason about the syntax of formal systems involving variable-binding operations. Inductively defined FM-sets involving the name-abstraction set former (together with Cartesian product and disjoint union) can correctly encode syntax modulo renaming of bound variables. In this way, the standard theory of algebraic data types can be extended to encompass signatures involving binding operators. In particular, there is an associated notion of structural recursion for defining syntax-manipulating functions (such as capture avoiding substitution, set of free variables, etc.) and a notion of proof by structural induction, both of which remain pleasingly close to informal practice in computer science. Received October 2000 / Accepted in revised form April 2001     

Simulating the Child's Acquisition of the Lexicon and Syntax—Experiences With Babel

This paper describes the theory and implementation ofBabel, a system which explores the hypothesis that much of the differences in the world's languages may be characterized by the inventory and properties of the lexical items and functional categories of those languages. The structure ofBabel assumes that functional categories are originally lacking in a child's syntax, and are acquired through a statistical induction process of lexical acquisition.Babel then uses information induced from the structure of the lexicon to create a model of syntax via a deductive, rule-based process. This model makes a number of predictions about the time course of language acquisition. These predictions are tested by runningBabel as a simulation of child language acquisition, using large samples of adult speech to children as input. The simulation results are shown to highly correlate to longitudinal studies of child language acquisition in English and Polish. Finally, the approach to handling noisy data withBabel is detailed.     

Implicit induction in conditional theories

We propose a new procedure for proof by induction in conditional theories where case analysis is simulated by term rewriting. This technique reduces considerably the number of variables of a conjecture to be considered for applying induction schemes. Our procedure is presented as a set of inference rules whose correctness has been formally proved. Moreover, when the axioms are ground convergent and the functions are completely defined, it is possible to apply the system for refuting conjectures. The procedure is even refutationally complete for conditional equations with Boolean preconditions over free constructors. The method is entirely implemented in the proverSPIKE. This system has solved interesting problems in a completely automatic way, that is, without interaction with the user and without ad hoc heuristics. It has also proved the challenging Gilbreath card trick, with only two easy lemmas.Preliminary versions of the results have been presented at the 13th International Joint Conference on Artificial Intelligence, Chambéry (France), 1993 (Bouhoula and Rusinowith, 1993).     

新型合金代铬刷镀层的组织及强化机理的研究

采用Ｘ射线衍射仪，透射电镜和扫描隧道显微镜等手段对新型代铬镀层（Ｎｉ－Ｆｅ－Ｗ－Ｐ－Ｓ）相结构及组织进行了研究，并初步探讨了镀层的强化机理。研究表明，Ｎｉ－Ｆｅ－Ｗ－Ｐ－Ｓ合金镀层的组织是由含Ｆｅ、Ｗ、Ｐ、Ｓ的镍基固溶体和在其上弥散分布的金属间化合物Ｎｉ_３Ｆｅ所组成，镍基固溶体处于非晶和微晶的混合状态，合金镀层的镀态硬度为ＨＶ７００～７５０，在３００℃退火时。硬度达到最大值ＨＶ９００～９５０，其强化机理主要是微晶的晶界强化和Ｎｉ_３Ｆｅ的弥散强化。     

KNOWLEDGE-BASED FEATURE DISCOVERY FOR EVALUATION FUNCTIONS

Since Samuel's work on checkers over thirty years ago, much effort has been devoted to learning evaluation functions. However, all such methods are sensitive to the feature set chosen to represent the examples. If the features do not capture aspects of the examples significant for problem solving, the learned evaluation function may be inaccurate or inconsistent. Typically, good feature sets are carefully handcrafted and a great deal of time and effort goes into refining and tuning them. This paper presents an automatic knowledge-based method for generating features for evaluation functions. The feature set is developed iteratively: features are generated, then evaluated, and this information is used to develop new features in turn. Both the contribution of a feature and its computational expense are considered in determining whether and how to develop it further.
This method has been applied to two problem-solving domains: the Othello board game and the domain of telecommunications network management. Empirical results show that the method is able to generate many known features and several novel features and to improve concept accuracy in both domains.     

风力发电与变流器

讨论了目前流行的两种主流风力发电系统：变速恒频双馈风力发电系统和永磁直驱同步风力发电系统。着重分析了两种风电变流器的拓扑结构、工作原理和性能特点,对风力发电系统发电机、变流器、无功支持和低电压穿越能力等方面进行了论述。     

基于统一硬化参量的海洋K0固结土动力本构模型

为方便海洋工程中桩土相互作用计算,根据海洋K₀固结土体特性,对现有相关土体本构模型进行简化。在修正剑桥模型的基础上,基于热力学理论,选用耗散功作为硬化参量,结合原状土体的固结属性,推导了适用于黏土与砂土的统一硬化模型。在此基础上,通过采用旋转硬化与等向硬化相结合的硬化理论来表征K₀固结土在循环荷载作用下的硬化规律,同时引入屈服面收缩参数Θ来描述循环荷载加载过程中土体屈服面的演化特性,进而建立了循环荷载下海洋K₀固结土体统一硬化模型。为验证本文提出的本构模型的合理性,开展了2个案例的对比研究,研究结果表明:新提出的统一硬化模型的计算值与实测值吻合,选用的计算参数少且物理意义明确。     

基于滑模变结构的感应电动机直接转矩控制

针对感应电动机常规直接转矩控制中存在磁链、转矩脉动大,低速控制不精确等问题,在建立α-β坐标系感应电动机数学模型的基础上,提出了一种基于滑模变结构的新型直接转矩控制方法。该方法利用转速滑模变结构控制器代替常规直接转矩控制中的PI控制器,可有效减小常规直接转矩控制中的磁链和转矩脉动,增强了系统的稳定性。仿真结果证明了该方法的正确性。     

基于灰色关联和D-S证据理论的感应电转子故障诊断

针对单一的灰色关联或D-S证据理论在转子故障诊断中存在的不足,将灰色关联和D-S证据理论相融合的决策级信息融合方法应用到感应电机转子故障诊断中;首先用灰色关联对故障进行初步诊断,然后,将灰色关联分析的诊断输出结果作为D-S证据理论的基本概率分配,最后,依据证据组合规则进行合成,得出转子故障的最终诊断结果;实验仿真结果验证了方法在转子故障诊断中的有效性,可以减小诊断的不确定性,提高故障的诊断准确率和诊断精度。     

Intelligent control of doubly‐fed induction generator systems using PIDNNs

An intelligent control for a stand‐alone doubly‐fed induction generator (DFIG) system using a proportional‐integral‐derivative neural network (PIDNN) is proposed in this study. This system can be applied as a stand‐alone power supply system or as the emergency power system when the electricity grid fails for all sub‐synchronous, synchronous, and super‐synchronous conditions. The rotor side converter is controlled using field‐oriented control to produce 3‐phase stator voltages with constant magnitude and frequency at different rotor speeds. Moreover, the grid side converter, which is also controlled using field‐oriented control, is primarily implemented to maintain the magnitude of the DC‐link voltage. Furthermore, the intelligent PIDNN controller is proposed for both the rotor and grid side converters to improve the transient and steady‐state responses of the DFIG system for different operating conditions. Both the network structure and online learning algorithm are introduced in detail. Finally, the feasibility of the proposed control scheme is verified through experimentation. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society