13,938 research outputs found
A novel hybrid technique for short-term electricity price forecasting in deregulated electricity markets
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Short-term electricity price forecasting is now crucial practice in deregulated electricity markets, as it forms the basis for maximizing the profits of the market participants. In this thesis, short-term electricity prices are forecast using three different predictor schemes, Artificial Neural Networks (ANNs), Support Vector Machine (SVM) and a hybrid scheme, respectively.
ANNs are the very popular and successful tools for practical forecasting. In this thesis, a hidden-layered feed-forward neural network with back-propagation has been adopted for detailed comparison with other forecasting models. SVM is a newly developed technique that has many attractive features and good performance in terms of prediction. In order to overcome the limitations of individual forecasting models, a hybrid technique that combines Fuzzy-C-Means (FCM) clustering and SVM regression algorithms is proposed to forecast the half-hour electricity prices in the UK electricity markets. According to the value of their power prices, thousands of the training data are classified by the unsupervised learning method of FCM clustering. SVM regression model is then applied to each cluster by taking advantage of the aggregated data information, which reduces the noise for each training program.
In order to demonstrate the predictive capability of the proposed model, ANNs and SVM models are presented and compared with the hybrid technique based on the same training and testing data sets in the case studies by using real electricity market data. The data was obtained upon request from APX Power UK for the year 2007.
Mean Absolute Percentage Error (MAPE) is used to analyze the forecasting errors of
different models and the results presented clearly show that the proposed hybrid
technique considerably improves the electricity price forecasting
Price Indexes For Multi-dwelling Properties In Sweden
No full textThe econometric test in this paper indicates that standard property and municipality attributes are important determinants of sales prices for MDCBs (multi-dwelling and commercial buildings) in Sweden. I also employ spatial econometric techniques and find that spatial specified regressions improved the models? explanatory power. The constant quality price for a model estimated with OLS is roughly one percentage point higher than for a model controlling for spatial autocorrelation. When the constant quality price trend is estimated on a yearly basis, there are hardly any differences between the estimated parameters, notwithstand-ing if all MDCBs are in the sample or if the sample is split into sub markets. However, estimating models with a quarterly constant quality price trend to some extent shows different price trends for the three sub markets.
NONCONSTANT PRICE EXPECTATIONS AND ACREAGE RESPONSE: THE CASE OF COTTON PRODUCTION IN GEORGIA
No full textAn adaptive regression model is used to examine the relative importance of cash and government support prices in determining cotton production over time. The results show that the cash price is more important as a source of price information for cotton producers than the government program price. The cash price was shown to have a greater influence on acreage response in every year, including periods thought to be dominated by government commodity programs.Adaptive regression, Cotton acreage response, Price expectations, Crop Production/Industries,
Price Rigidity and Flexibility: Recent Theoretical Developments
No full textThe price system, the adjustment of prices to changes in market conditions, is the primary mechanism by which markets function and by which the three most basic questions get answered: what to produce, how much to produce and for whom to produce. To the behaviour of price and price system, therefore, have fundamental implications for many key issues in microeconomics and industrial organization, as well as in macroeconomics and monetary economics. In microeconomics, managerial economics, and industrial organization, economists focus on the price system efficiency. In macroeconomics and monetary economics, economists focus on the extent to which nominal prices fail to adjust to changes in market conditions. Nominal price rigidities play particularly important role in modern monetary economics and in the conduct of monetary policy because of their ability to explain short-run monetary non-neutrality. The behaviour of prices, and in particular the extent of their rigidity and flexibility, therefore, is of central importance in economics. This introductory essay briefly summarizes the eight studies of price rigidity that are included in this special issue.Price Rigidity; Price Flexibility; Cost of Price Adjustment; Menu Cost; Managerial and Customer Cost of Price Adjustment; New Keynesian Economics; Price System
GA-Fuzzy PID control simulation waveform diagram.
No full textAs is well known, the metal annealing process has the characteristics of heat concentration and rapid heating. Traditional vacuum annealing furnaces use PID control method, which has problems such as high temperature fluctuation, large overshoot, and long response time during the heating and heating process. Based on this situation, some domestic scholars have adopted fuzzy PID control algorithm in the temperature control of vacuum annealing furnaces. Due to the fact that fuzzy rules are formulated through a large amount of on-site temperature data and experience summary, there is a certain degree of subjectivity, which cannot ensure that each rule is optimal. In response to this drawback, the author combined the technical parameters of vacuum annealing furnace equipment, The fuzzy PID temperature control of the vacuum annealing furnace is optimized using genetic algorithm. Through simulation and comparative analysis, it is concluded that the design of the fuzzy PID vacuum annealing furnace temperature control system based on GA optimization is superior to fuzzy PID and traditional PID control in terms of temperature accuracy, rise time, and overshoot control. Finally, it was verified through offline experiments that the fuzzy PID temperature control system based on GA optimization meets the annealing temperature requirements of metal workpieces and can be applied to the temperature control system of vacuum annealing furnaces.</div
Price Memorial Hall, Dahlonega, GA
No full textPrice Memorial Hall, Dahlonega, GA. Dahlonega is a city in and the county seat of Lumpkin County, Georgia, United States. Erected here in 1837 was a U.S. Branch Mint which operated until seized by the Confederates in 1861. In 1871 the mint building and ten acres of land were transferred to the state for use as an agricultural college, largely through the efforts in Congress of Representative William Pierce Price, founder of North Georgia College and President of its Board of Trustees until his death in 1908. The mint building was destroyed by fire in 1878 The new structure came to serve as the college administration building and in 1934 by action of the state Board of Regents was named the Price Memorial Building to honor the founder. Leafing of the steeple with gold from the surrounding hills was sponsored by the Dahlonega Club to commemorate in 1973 the 100th anniversary of the college.It was included in the National Register of Historic Places NRIS #72000387https://digitalcommons.unf.edu/historical_architecture_main/2089/thumbnail.jp
Oral history interview with Robert L. Price, November 1, 1999
No full text1 electronic record(s) and derivatives. XXX audio file (wav, mp3) 545760906 bytes. 00:22:10. 3 PDF documents (3 scans, jp2). 1 digital photograph. 582 MB (610,933,400 bytes).Oral history interview with Robert L. Price, November 1, 1999. Valdosta (Ga.). Fieldworker: Latasha N. McCoy. Audio file. Part of the South Georgia Folklife Project at Valdosta State University Archives and Special Collections.
Note: Poor audio quality
Feature selection and parameter optimization with GA-LSSVM in electricity price forecasting
No full textForecasting price has now become essential
task in the operation of electrical power system. Power
producers and customers use short term price forecasts
to manage and plan for bidding approaches, and hence
increasing the utility’s profit and energy efficiency as
well. The main challenge in forecasting electricity price
is when dealing with non-stationary and high volatile
price series. Some of the factors influencing this
volatility are load behavior, weather, fuel price and
transaction of import and export due to long term
contract. This paper proposes the use of Least Square
Support Vector Machine (LSSVM) with Genetic
Algorithm (GA) optimization technique to predict daily
electricity prices in Ontario. The selection of input data
and LSSVM’s parameter held by GA are proven to
improve accuracy as well as efficiency of prediction. A
comparative study of proposed approach with other
techniques and previous research was conducted in term
of forecast accuracy, where the results indicate that (1)
the LSSVM with GA outperforms other methods of
LSSVM and Neural Network (NN), (2) the optimization
algorithm of GA gives better accuracy than Particle
Swarm Optimization (PSO) and cross validation.
However, future study should emphasize on improving
forecast accuracy during spike event since Ontario
power market is reported as among the most volatile
market worldwide
Price competition between an expert and a non-expert
No full textprice competition;product differentiation;quality
Auctions with Almost Homogeneous Bidders
No full textWe deviate from the symmetric case of the independent private value model by allowing the bidders’ value distributions, which depend on parameters, to be slightly different. We show that previous results about the equality to the first-order in the parameters between revenues from the second-price auction and other auction mechanisms follow from the joint differentiability of the equilibria with respect to the parameters. We prove this differentiability for the first-price auction and obtain general formulas for the different first-order effects. From our results about the first-price auction, we analytically generate examples with continuous distributions where a stochastic improvement to a bidder’s value distribution reduces his equilibrium payoff. In another application, we show that, starting from competition among cartels of equal sizes, allowing in a small number of members from other cartels can be profitable only if the members or the synergies between them are strong enough.Independent private value model; auctions; asymmetry; first-price auction, second-price auction; differentiability; revenue equivalence theorem
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