Model-free Prediction based on Tracking Theory and Newton Form of Polynomial

The majority of existing predictors for time series are model-dependent and therefore require some prior knowledge for the identification of complex systems, usually involving system identification, extensive training, or online adaptation in the case of time-varying systems. Additionally, since a time series is usually generated by complex processes such as the stock market or other chaotic systems, identification, modeling or the online updating of parameters can be problematic. In this paper a model-free predictor (MFP) for a time series produced by an unknown nonlinear system or process is derived using tracking theory. An identical derivation of the MFP using the property of the Newton form of the interpolating polynomial is also presented. The MFP is able to accurately predict future values of a time series, is stable, has few tuning parameters and is desirable for engineering applications due to its simplicity, fast prediction speed and extremely low computational load. The performance of the proposed MFP is demonstrated using the prediction of the Dow Jones Industrial Average stock index.

Silicon Application and Nitrogen on Yield and Yield Components in Rice (Oryza sativa L.) in Two Irrigation Systems

Silicon is a beneficial element for plant growth. It helps plants to overcome multiple stresses, alleviates metal toxicity and improves nutrient imbalance. Field experiment was conducted as split-split plot arranged in a randomized complete block design with four replications. Irrigation system include continues flooding and deficit as main plots and nitrogen rates N0, N46, N92, and N138 kg/ha as sub plots and silicon rates Si0 & Si500 kg/ha as sub-subplots. Results indicate that grain yield had not significant difference between irrigation systems. Flooding irrigation had higher biological yield than deficit irrigation whereas, no significant difference in grain and straw yield. Nitrogen application increased grain, biological and straw yield. Silicon application increased grain, biological and straw yield but, decreased harvest index. Flooding irrigation had higher number of total tillers / hill than deficit irrigation, but deficit irrigation had higher number of fertile tillers / hill than flooding irrigation. Silicon increased number of filled spikelet and decreased blank spikelet. With high nitrogen application decreased 1000-grain weight. It can be concluded that if the nitrogen application was high and water supplied was available we could have silicon application until increase grain yield.

Investigation of Water Deficit Stress on Agronomical Traits of Soybean Cultivars in Temperate Climate

In order to investigate water deficit stress on 24 of soybean (Glycine Max. L) cultivars and lines in temperate climate, an experiment was conducted in Iran Seed and Plant Improvement Institute. Stress levels were irrigation after evaporation of 50, 100, 150 mm water from pan, class A. Randomized Completely Block Design was arranged for each stress levels. Some traits such as, node number, plant height, pod number per area, grain number per pod, grain number per area, 1000 grains weight, grain yield and harvest index were measured. Results showed that water deficit stress had significant effect on node number, plant height, pod number per area, grain number per pod, grain number per area, 1000 grains weight and harvest index. Also all of agronomic traits except harvest index influenced significantly by cultivars and lines. The least and most grain yield was belonged to Ronak X Williams and M41 x Clark respectively.

Compression of Semistructured Documents

EGOTHOR is a search engine that indexes the Web and allows us to search the Web documents. Its hit list contains URL and title of the hits, and also some snippet which tries to shortly show a match. The snippet can be almost always assembled by an algorithm that has a full knowledge of the original document (mostly HTML page). It implies that the search engine is required to store the full text of the documents as a part of the index. Such a requirement leads us to pick up an appropriate compression algorithm which would reduce the space demand. One of the solutions could be to use common compression methods, for instance gzip or bzip2, but it might be preferable if we develop a new method which would take advantage of the document structure, or rather, the textual character of the documents. There already exist a special compression text algorithms and methods for a compression of XML documents. The aim of this paper is an integration of the two approaches to achieve an optimal level of the compression ratio

Creativity and Economic Development

The objective of this paper is to construct a creativity composite index designed to capture the growing role of creativity in driving economic and social development for the 27 European Union countries. The paper proposes a new approach for the measurement of EU-27 creative potential and for determining its capacity to attract and develop creative human capital. We apply a modified version of the 3T model developed by Richard Florida and Irene Tinagli for constructing a Euro-Creativity Index. The resulting indexes establish a quantitative base for policy makers, supporting their efforts to determine the contribution of creativity to economic development.

Comparative Analysis of Concentration in Insurance Markets in New EU Member States

The purpose of this article is to analyze the market structure as well as the degree of concentration in insurance markets in new EU member states. The analysis was conducted using several most commonly used concentration indicators such as concentration ratio, Herfindahl-Hirschman index and entropy index. These indicators were calculated for the 2000-2010 period on the basis of total gross written premium as the most relevant indicator of market power in insurance markets. The results of the analysis showed that in all observed countries the level of concentration decreased, though with significantly different intensity. Yet, in some countries, the level of concentration remains very high.

Using Data Mining Methodology to Build the Predictive Model of Gold Passbook Price

Gold passbook is an investing tool that is especially suitable for investors to do small investment in the solid gold. The gold passbook has the lower risk than other ways investing in gold, but its price is still affected by gold price. However, there are many factors can cause influences on gold price. Therefore, building a model to predict the price of gold passbook can both reduce the risk of investment and increase the benefits. This study investigates the important factors that influence the gold passbook price, and utilize the Group Method of Data Handling (GMDH) to build the predictive model. This method can not only obtain the significant variables but also perform well in prediction. Finally, the significant variables of gold passbook price, which can be predicted by GMDH, are US dollar exchange rate, international petroleum price, unemployment rate, whole sale price index, rediscount rate, foreign exchange reserves, misery index, prosperity coincident index and industrial index.

Automatic Generation Control of an Interconnected Power System with Capacitive Energy Storage

This paper is concerned with the application of small rating Capacitive Energy Storage units for the improvement of Automatic Generation Control of a multiunit multiarea power system. Generation Rate Constraints are also considered in the investigations. Integral Squared Error technique is used to obtain the optimal integral gain settings by minimizing a quadratic performance index. Simulation studies reveal that with CES units, the deviations in area frequencies and inter-area tie-power are considerably improved in terms of peak deviations and settling time as compared to that obtained without CES units.

Decision Trees for Predicting Risk of Mortality using Routinely Collected Data

It is well known that Logistic Regression is the gold standard method for predicting clinical outcome, especially predicting risk of mortality. In this paper, the Decision Tree method has been proposed to solve specific problems that commonly use Logistic Regression as a solution. The Biochemistry and Haematology Outcome Model (BHOM) dataset obtained from Portsmouth NHS Hospital from 1 January to 31 December 2001 was divided into four subsets. One subset of training data was used to generate a model, and the model obtained was then applied to three testing datasets. The performance of each model from both methods was then compared using calibration (the χ2 test or chi-test) and discrimination (area under ROC curve or c-index). The experiment presented that both methods have reasonable results in the case of the c-index. However, in some cases the calibration value (χ2) obtained quite a high result. After conducting experiments and investigating the advantages and disadvantages of each method, we can conclude that Decision Trees can be seen as a worthy alternative to Logistic Regression in the area of Data Mining.