对厦门市2000年前电力需求的预测与评论

本文通过80～90年代厦门国内生产总值统计,根据93年制订的厦门国内生产总值规划指标,采用回归分析法,对厦门90年代到2000年止的电力需求,人均国民经济收入,以及人均电耗等重要指标做出预测,并与某此工业先进国家或地区进行横向比较,进而提出笔者对2000年前发展电力事业的建设性见解。

Discrete-time Markov-based dynamic control approach for compressed sampling

To solve the problem that the signal sparsity level is time-varying and not known as a priori in most cases,a signal sparsity level prediction and optimal sampling rate determination scheme is proposed.The discrete-time Markov chain is used to model the signal sparsity level and analyze the transition between different states.According to the current state,the signal sparsity level state in the next sampling period and its probability are predicted.Furthermore,based on the prediction results,a dynamic control approach is proposed to find out the optimal sampling rate with the aim of maximizing the expected reward which considers both the energy consumption and the recovery accuracy.The proposed approach can balance the tradeoff between the energy consumption and the recovery accuracy.Simulation results show that the proposed dynamic control approach can significantly improve the sampling performance compared with the existing approach.

Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System

Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.

产品市场力量与财务分析师盈余预测

本文研究了上市公司产品市场力量对财务分析师盈余预测行为的影响。以中国2002-2011年11857个上市公司年观测为样本,研究发现,财务分析师更倾向于关注那些具有较强产品市场力量(处于高集中度行业、产品定价力量较强或者在行业内所占市场份额较高)的上市公司,对于这类上市公司,财务分析师盈余预测的离散度更低、准确度更高。本研究不仅有助于深入理解我国财务分析师的盈余预测行为,对投资者更有效地利用财务分析师的盈余预测也具有借鉴意义。

Predictability of Functional Diversity Depends on the Number of Traits

Analysis of functional diversity, based on plant traits and community structure, provides a promising approach for exploration of the adaptive strategies of plants and the relationship between plant traits and ecosystem functioning. However, it is unclear how the number of plant traits included influences functional diversity, and whether or not there are quantitatively dependent traits. This information is fundamental to the correct use of functional diversity metrics. Here, we measured 34 traits of 366 plant species in nine forests from the tropical to boreal zones in China. These traits were used to calculate seven functional diversity metrics: functional richness(functional attribute diversity(FAD), modified FAD(MFAD), convex hull hypervolume(FRic)), functional evenness(FEve), and functional divergence(functional divergence(FDiv), functional dispersion(FDis), quadratic entropy(Rao Q)). Functional richness metrics increased with an increase in trait number, whereas the relationships between the trait divergence indexes(FDiv and FDis) and trait number were inconsistent. Four of the seven functional diversity indexes(FAD, MFAD, FRic, and RaoQ) were comparable with those in previous studies, showing predictable trends with a change in trait number. We verified our hypothesis that the number of traits strongly influences functional diversity. The relationships between these predictable functional diversity metrics and the number of traits facilitated the development of a standard protocol to enhance comparability across different studies. These findings can support integration of functional diversity index data from different studies at the site to the regional scale, and they focus attention on the influence of quantitative selection of traits on functional diversity analysis.

A New Grey Model Based on Optimizing the Grey Derivative and the Background Value at the Same Time

Based on both white response and connotation expression are geometric progression in the most primitive grey differential equation of GM（1,1）x（k） （k）＋ ax（1） （k） = b, this paper begins with generation of the time response .function＇s grey derivative at discrete points. Through derivative＇s definition, establishing a new GM（1,1） by optimizing grey derivative and background value. Then, getting the best coefficient c by introducing criterion function and it has proved that the new expression has the whitened exponent law coincident property and the whitened coefficient coincident property in theory. Finally, some examples show the new model has higher prediction precision.