煤矿智能化建设探索与实践

分析了煤矿智能化建设的重要意义和必要性,从示范工程建设大力推进、产学研用融合发展不断深入、完善顶层设计及其企业支持政策、建立健全相关标准机制等方面阐述了目前煤矿智能化建设的初步成效,剖析了在基础理论、技术标准、核心装备、煤矿智能化匹配高端人才等方面存在的问题,从保障能力、科技攻关、工程建设等方面介绍了中煤能源集团煤矿智能化建设的实践和进展,并提出全面推进生产智能化、加快建设“数字中煤”、持续强化关键技术攻关、着力提升自主创新能力等煤矿智能化建设的下一步重点任务。     

基于灰色预测模型电火花线切割工艺参数优化

针对电火花线切割加工机制的不确定性,工艺参数与工艺指标具有高度非线性关系;设计正交实验,分析脉宽、占空比、加工电流、丝速和跟踪系数对SKD?11材料去除率（ MRR）的影响;分别建立逐次广义回归模型（ GRM）和灰色预测模型（ GFM）,并对两个模型进行实验验证和比较,寻求出最佳的工艺参数。验证实验表明,所建立的灰色预测模型（ GFM）能够对实际加工的材料去除率（ MRR）进行精确的预测。     

基于广义马尔科夫链模型的动柔度预测

动柔度对机械加工的稳定性和精度有重要的影响。对动柔度进行预测能为机床加工精度补偿和稳定性分析提供实际的指导作用。由于不确定性的存在会降低结果的可靠性与可信度,传统的马尔科夫链预测方法没有考虑不确定性问题。为了提高预测结果的可靠性与可信度,在马尔科夫链模型的基础上提出了一个广义马尔科夫链模型,并通过广义马尔科夫链模型对动柔度进行了预测。结果表明：提出的预测方法有一个好的预测性能。     

基于GA-GRNN的地表下沉系数预测方法研究

将遗传算法(GA)和广义回归神经网络(GRNN)方法进行融合,采用GA算法搜寻最优的GRNN光滑因子,简要分析了地表下沉系数的影响因素,建立了基于GA-GRNN的地表下沉系数预测模型。以我国典型观测站的数据资料作为学习和测试样本,将预测结果与实测值进行比较。结果表明:采用GA-GRNN模型预测地表下沉系数能够综合考虑诸多的地质采矿因素,预测结果与实测值得最大相对误差仅为5.44%,完全满足现场工程的需要,为今后预测地表下沉系数提出了一种新的方法。     

科学深孔复杂地层钻进技术难题与对策

介绍了在复杂地层科学深钻施工时遇到的困难和问题,主要包括破碎地层钻进问题和强缩径地层钻进问题,讨论了解决这些技术难题时采取的应对技术方案和措施,涉及取心钻进工艺方法和器具、钻机、泥浆体系以及极破碎、强缩径地层的特殊钻进、固井工艺和器具。     

A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS ³) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.     

Some evaluations of basic nodal-like schemes for a selection of classical problems in particle transport theory

In order to provide some basic evaluations of elementary nodal techniques, as used in the general area of particle transport theory, critical and albedo problems for cylinders, spheres, and slabs are solved approximately in terms of averaged quantities and compared to exact results.     

Generalized weighted likelihood density estimators with application to finite mixture of exponential family distributions

The family of weighted likelihood estimators largely overlaps with minimum divergence estimators. They are robust to data contaminations compared to MLE. We define the class of generalized weighted likelihood estimators (GWLE), provide its influence function and discuss the efficiency requirements. We introduce a new truncated cubic-inverse weight, which is both first and second order efficient and more robust than previously reported weights. We also discuss new ways of selecting the smoothing bandwidth and weighted starting values for the iterative algorithm. The advantage of the truncated cubic-inverse weight is illustrated in a simulation study of three-component normal mixtures model with large overlaps and heavy contaminations. A real data example is also provided.     

Shorter strings containing all k-element permutations

We consider the problem of finding short strings that contain all permutations of order k over an alphabet of size n, with k?n. We show constructively that k(n−2)+3 is an upper bound on the length of shortest such strings, for n?k?10. Consequently, for n?10, the shortest strings that contain all permutations of order n have length at most n²−2n+3. These two new upper bounds improve with one unit the previous known upper bounds.     

广义计算系统研究

该文简要介绍运用广义计算技术而建立起来的一类人工智能系统──广义计算系统，包括广义计算系统的数学描述，广义计算系统的实现问题和学习问题。