Introduction:Nowadays,the most significant challenges in the stock market is to predict the stock prices.The stock price data represents a financial time series data which becomes more difficult to predict due to its ...Introduction:Nowadays,the most significant challenges in the stock market is to predict the stock prices.The stock price data represents a financial time series data which becomes more difficult to predict due to its characteristics and dynamic nature.Case description:Support Vector Machines(SVM)and Artificial Neural Networks(ANN)are widely used for prediction of stock prices and its movements.Every algorithm has its way of learning patterns and then predicting.Artificial Neural Network(ANN)is a popular method which also incorporate technical analysis for making predictions in financial markets.Discussion and evaluation:Most common techniques used in the forecasting of financial time series are Support Vector Machine(SVM),Support Vector Regression(SVR)and Back Propagation Neural Network(BPNN).In this article,we use neural networks based on three different learning algorithms,i.e.,Levenberg-Marquardt,Scaled Conjugate Gradient and Bayesian Regularization for stock market prediction based on tick data as well as 15-min data of an Indian company and their results compared.Conclusion:All three algorithms provide an accuracy of 99.9%using tick data.The accuracy over 15-min dataset drops to 96.2%,97.0%and 98.9%for LM,SCG and Bayesian Regularization respectively which is significantly poor in comparison with that of results obtained using tick data.展开更多
The mites found in stored food and house comprise a large group of subclass Acari, belonging to the suborder Acardida of the order Acarifornes. They can be found in dust and vacuum samples from floors, furniture, matt...The mites found in stored food and house comprise a large group of subclass Acari, belonging to the suborder Acardida of the order Acarifornes. They can be found in dust and vacuum samples from floors, furniture, mattresses, Chinese herbal medicine, dry fruit, grain, flour, sugar, and bedding. These mites are nidicolous and feed on organic debris, including sloughed human skin, fungi, spilled food, pollen, etc. These mites are particularly prevalent in Chinese herbal medicine, dry fruit, grain, flour, sugar, beds, though carpeted floors near beds or couches may also have large numbers. The most common species are Acarus siro, Tyrophagus putrescentiae , Dermatophagoides farinae , D . pteronyssinus, Glycyphagus domesticus, G. Ornatus, Carpoglyphus lactis and Tarsonemus granarius, etc. The viability of mites in storage is quite strong and they can invade and parasitize the intestines of humans[1 -15]. They can cause pulmonary acariasis[16-25] , urinary acariasis[26-33] and so on. The dejecta of mites is a quite strong allergen and can cause different allergic diseases[34-44]. Intestinal acariasis can be caused by some mites related to the way of diet intake and invading against intestinal mucosa, intestinal muscle[45-5a]. The first report of intestinal acariasis caused by these mites was made by Hinman et al (1934)[45]. From then on, all kinds of studies on the disease have been reported gradually. In order to make an epidemiological survey of intestinal acariasis the investigation of the disease was taken in some areas of Anhui Province from 1989 to 1996.展开更多
文摘Introduction:Nowadays,the most significant challenges in the stock market is to predict the stock prices.The stock price data represents a financial time series data which becomes more difficult to predict due to its characteristics and dynamic nature.Case description:Support Vector Machines(SVM)and Artificial Neural Networks(ANN)are widely used for prediction of stock prices and its movements.Every algorithm has its way of learning patterns and then predicting.Artificial Neural Network(ANN)is a popular method which also incorporate technical analysis for making predictions in financial markets.Discussion and evaluation:Most common techniques used in the forecasting of financial time series are Support Vector Machine(SVM),Support Vector Regression(SVR)and Back Propagation Neural Network(BPNN).In this article,we use neural networks based on three different learning algorithms,i.e.,Levenberg-Marquardt,Scaled Conjugate Gradient and Bayesian Regularization for stock market prediction based on tick data as well as 15-min data of an Indian company and their results compared.Conclusion:All three algorithms provide an accuracy of 99.9%using tick data.The accuracy over 15-min dataset drops to 96.2%,97.0%and 98.9%for LM,SCG and Bayesian Regularization respectively which is significantly poor in comparison with that of results obtained using tick data.
基金the grants from Science Foundation of the Ministry of Coal Industry of China
文摘The mites found in stored food and house comprise a large group of subclass Acari, belonging to the suborder Acardida of the order Acarifornes. They can be found in dust and vacuum samples from floors, furniture, mattresses, Chinese herbal medicine, dry fruit, grain, flour, sugar, and bedding. These mites are nidicolous and feed on organic debris, including sloughed human skin, fungi, spilled food, pollen, etc. These mites are particularly prevalent in Chinese herbal medicine, dry fruit, grain, flour, sugar, beds, though carpeted floors near beds or couches may also have large numbers. The most common species are Acarus siro, Tyrophagus putrescentiae , Dermatophagoides farinae , D . pteronyssinus, Glycyphagus domesticus, G. Ornatus, Carpoglyphus lactis and Tarsonemus granarius, etc. The viability of mites in storage is quite strong and they can invade and parasitize the intestines of humans[1 -15]. They can cause pulmonary acariasis[16-25] , urinary acariasis[26-33] and so on. The dejecta of mites is a quite strong allergen and can cause different allergic diseases[34-44]. Intestinal acariasis can be caused by some mites related to the way of diet intake and invading against intestinal mucosa, intestinal muscle[45-5a]. The first report of intestinal acariasis caused by these mites was made by Hinman et al (1934)[45]. From then on, all kinds of studies on the disease have been reported gradually. In order to make an epidemiological survey of intestinal acariasis the investigation of the disease was taken in some areas of Anhui Province from 1989 to 1996.
