Forecasting nonlinear time series with feed‐forward neural networks: a case study of Canadian lynx data

The forecasting capabilities of feed‐forward neural network (FFNN) models are compared to those of other competing time series models by carrying out forecasting experiments. As demonstrated by the detailed forecasting results for the Canadian lynx data set, FFNN models perform very well, especially when the series contains nonlinear and non‐Gaussian characteristics. To compare the forecasting accuracy of a FFNN model with an alternative model, Pitman's test is employed to ascertain if one model forecasts significantly better than another when generating one‐step‐ahead forecasts. Moreover, the residual‐fit spread plot is utilized in a novel fashion in this paper to compare visually out‐of‐sample forecasts of two alternative forecasting models. Finally, forecasting findings on the lynx data are used to explain under what conditions one would expect FFNN models to furnish reliable and accurate forecasts. Copyright © 2005 John Wiley & Sons, Ltd.     

中文报刊广告妙语英译策略探索

本文从广告翻译的目的出发,认为中文报刊广告妙语翻译的原则应该是"读者至上",即在翻译时对原文作适当变通,发挥译语优势,让译语读者对译文广告知之、好之、乐之,从而促进产品销售,让译文和原文达到"功能对等"。     

Rate-compensated synaptic events in antarctic fish: Consequences of homeoviscous cold-adaptation

Summary At ambient sub-zero temperatures, muscles from antarctic fish produce spontaneous postsynaptic currents (MEPCs) of significantly shorter duration than those of temperate fishes. Fast decay of antarctic MEPCs is a predictable consequence of the increased membrane fluidity attributable to fatty acid unsaturation in cold-adapted animals.We wish to thank the Antarctic Division of the New Zealand Department of Scientific and Industrial Research, and the staff of Scott Base, without whom this work could not have been done. The work was supported financially by grants from the New Zealand University Grants Committee and from the Auckland University Research Committee. We are also grateful to members of the United States Antarctic Research Program, in particular Dr A. L. DeVries, for advice and assistance.     

欧盟反规避措施与中国企业无效规避问题探究

随着中国外向型经济的发展,中国与欧盟的经贸往来日益频繁,同时中国出口企业也遭到了越来越多的欧盟反倾销指控,而中国出口企业在寻求规避反倾销时,由于没有注意欧盟反规避立法反而形成“无效规避”,并遭受到反规避制裁。文章通过对欧盟反规避条款的分析为中国出口企业进行有效规避提出建议。     

对话:精神传承与形式转换--从夏衍电影改编实践看一种改编观念

改编并不是简单的从文学到电影的形式转换,而是一次"对话".既是与已经成为"历史"的原作的"对话",也是与正在发展的"现实"的"对话";既是与原作者的"对话",也是与未来影片的潜在接受者的"对话".由于时代、历史、文化背景的差异,由于两种艺术形式、两种传播媒介的差异,也由于创作者(包括原作者和改编者)艺术个性、审美趣味、生活经历等等各方面的差异,原作者和改编者之间势必存在两套不同的语言表达系统.改编的过程也是在两者的矛盾冲撞中竭力寻求平衡的过程,是在裂隙间寻找符合现时社会文化所需要的语言表意符码的过程,这就是所谓的"对话".同时,由于文字语言思维与视听语言思维本身存在的差异,"对话"事实上也是两种艺术形式、两种传播媒介之间的碰撞.夏衍"建国17年"的改编实践在精神主旨和艺术形式两个层面上,成功地完成了与原作和原作者的"对话",既相对准确地传达出原作的精神主旨,又在剧作的角度创造性地完成了形式的转换--从小说到电影.更重要的是,夏衍的改编实践还完成了与主流意识形态的"对话",从电影创作方面为新的意识形态的确立提供了引人注目的"范本".     

Overview: development in bacteria: spore formation in Bacillus subtilis

Like eukaryotes, bacteria possess complex developmental programs that drive environmental adaptation and morphological differentiation. In some species, these morphological changes are quite elaborate and result in major changes in cell appearance, including the formation of ornate appendages. The ease with which some bacteria can be manipulated makes them highly attractive model systems for developmental analysis. In this set of reviews, we tackle the best studied of these systems, spore formation in Bacillus subtilis. Construction of a spore initiates in response to starvation, takes each cell about 8 h and is directed by a tightly controlled genetic program. First, the cell creates an internal protoplast with its own copy of the chromosome. Over the next several hours, development continues as proteins synthesized within the protoplast as well as in the surrounding cell cytoplasm coalesce into the various complex structures that comprise the spore. The resulting cell is metabolically dormant and as close to indestructible as any cell found on earth. Nonetheless, the spore retains the ability to revive almost immediately when nutrient returns to the environment. Here, we review the genetic control of spore formation, the structure and assembly of several major spore components, the process of germination, and the environmental and disease implications of spores. As these reviews document, spore formation in B. subtilis has been among the most productive systems for understanding both the broad themes and the molecular basis of development. Not only does this system continue to add to our understanding of these questions, but it provides a particularly powerful means to address the cell biological dimension of development.     

Parsimonious modeling and forecasting of corporate yield curve

This paper investigates the sensitivity of out‐of‐sample forecasting performance over a span of different parameters of l in the dynamic Nelson–Siegel three‐factor AR(1) model. First, we find that the ad hoc selection of l is not optimal. Second, we find a substantial difference in factor dynamics between investment‐grade and speculative‐grade corporate bonds from 1994:12 to 2006: 4. Third, we suggest that the three‐factor model is sufficient to explain the main variations of corporate yield changes. Finally, the parsimonious Nelson–Siegel three‐factor AR(1) model remains competitive in the out‐of‐sample forecasting of corporate yields. Copyright © 2008 John Wiley & Sons, Ltd.     

Mortality forecasting using neural networks and an application to cause‐specific data for insurance purposes

Mortality forecasting is important for life insurance policies, as well as in other areas. Current techniques for forecasting mortality in the USA involve the use of the Lee–Carter model, which is primarily used without regard to cause. A method for forecasting morality is proposed which involves the use of neural networks. A comparative analysis is done between the Lee–Carter model, linear trend and the proposed method. The results confirm that the use of neural networks performs better than the Lee–Carter and linear trend model within 5% error. Furthermore, mortality rates and life expectancy were formulated for individuals with a specific cause based on prevalence data. The rates are broken down further into respective stages (cancer) based on the individual's diagnosis. Therefore, this approach allows life expectancy to be calculated based on an individual's state of health. Copyright © 2008 John Wiley & Sons, Ltd.     

Efficient forecasting in nearly non‐stationary processes

This paper proposes a procedure to make efficient predictions in a nearly non‐stationary process. The method is based on the adaptation of the theory of optimal combination of forecasts to nearly non‐stationary processes. The proposed combination method is simple to apply and has a better performance than classical combination procedures. It also has better average performance than a differenced predictor, a fractional differenced predictor, or an optimal unit‐root pretest predictor. In the case of a process that has a zero mean, only the non‐differenced predictor is slightly better than the proposed combination method. In the general case of a non‐zero mean, the proposed combination method has a better overall performance than all its competitors. Copyright © 2002 John Wiley & Sons, Ltd.     

A fractal forecasting model for financial time series

Financial market time series exhibit high degrees of non‐linear variability, and frequently have fractal properties. When the fractal dimension of a time series is non‐integer, this is associated with two features: (1) inhomogeneity—extreme fluctuations at irregular intervals, and (2) scaling symmetries—proportionality relationships between fluctuations over different separation distances. In multivariate systems such as financial markets, fractality is stochastic rather than deterministic, and generally originates as a result of multiplicative interactions. Volatility diffusion models with multiple stochastic factors can generate fractal structures. In some cases, such as exchange rates, the underlying structural equation also gives rise to fractality. Fractal principles can be used to develop forecasting algorithms. The forecasting method that yields the best results here is the state transition‐fitted residual scale ratio (ST‐FRSR) model. A state transition model is used to predict the conditional probability of extreme events. Ratios of rates of change at proximate separation distances are used to parameterize the scaling symmetries. Forecasting experiments are run using intraday exchange rate futures contracts measured at 15‐minute intervals. The overall forecast error is reduced on average by up to 7% and in one instance by nearly a quarter. However, the forecast error during the outlying events is reduced by 39% to 57%. The ST‐FRSR reduces the predictive error primarily by capturing extreme fluctuations more accurately. Copyright © 2004 John Wiley & Sons, Ltd.