scholarly journals Statistical analysis of music data

2011 ◽  
Vol 52 ◽  
Author(s):  
Mindaugas Kavaliauskas
Keyword(s):  
Time Series ◽  
Markov Chain ◽  
Statistical Analysis ◽  
Data Clustering ◽  
Mathematical Methods ◽  
Markov Chain Models ◽  
Tight Connection ◽  
Music And Mathematics ◽  
And Mathematics ◽  
Work Done

Connection of music and mathematics is known from Pythagoras. Music sounds are in harmony if it satisfies certain mathematical conditions. Despite tight connection between music and mathematics, the idea of using mathematical methods in musicology was used only in the 1950s. Last decade various methods of mathematical statistics, such as correlation analysis, time series analysis, analysis of variance, data clustering, Markov chain models was successfully applied in musiclogy. Though, there was no work done in this area in Lithuania. In this article musical data (notes) is analysed using statistical methods. Musical intervalas are analysed. Music compositions are classified. Analysis results are presented. Research uses works of a few Lithuanian composers.  

Markov Chain for Predicting of Annual Precipitation Based on Entropy Weight

2012 ◽  
Vol 518-523 ◽  
pp. 4034-4038
Author(s):  
Zhan Qing Ma ◽  
Yong Mei Xie ◽  
Shu Yao Wen
Keyword(s):  
Time Series ◽  
Markov Chain ◽  
Prediction Accuracy ◽  
Absolute Error ◽  
Annual Precipitation ◽  
Entropy Weight ◽  
Markov Chain Models ◽  
Precipitation Prediction ◽  
Markov Chain Method ◽  
Weight Data

Aimed at the feature of annual precipitation,this paper puts forward a predicting Markov chain method based on entropy weight. Data of precipitation in Hangzhou,from 1956 to 2009,was used as an example. The precipitation can be predicted year by year using the Markov chain models based on entropy weight. Hangzhou past 5 years the results of precipitation yearly basis,respectively：the absolute error of 73mm,27mm,-22mm,-17mm and 20mm;the relative error was 5.66%, 2.03%,-1.59%,-1.08% and 1.30%.The error value of smaller than ±5％ and ±10％ was 36.67% and 60.00% respectively in the 30 years of precipitation prediction. M-K test was applied for nearly 30 years of predicting results for time series analysis, the results show that the prediction data with the increase in prediction accuracy tends to gradually increase.

First and second order Markov chain models for synthetic generation of wind speed time series

Energy ◽  
2005 ◽  
Vol 30 (5) ◽  
pp. 693-708 ◽  
Author(s):  
A SHAMSHAD ◽  
M BAWADI ◽  
W WANHUSSIN ◽  
T MAJID ◽  
S SANUSI
Keyword(s):  
Time Series ◽  
Markov Chain ◽  
Wind Speed ◽  
Second Order ◽  
Markov Chain Models ◽  
Order Markov Chain ◽  
Synthetic Generation

Exceptional Motifs in Different Markov Chain Models for a Statistical Analysis of DNA Sequences

1995 ◽  
Vol 2 (3) ◽  
pp. 417-437 ◽  
Author(s):  
SOPHIE SCHBATH ◽  
BERNARD PRUM ◽  
ELISABETH DE TURCKHEIM
Keyword(s):  
Markov Chain ◽  
Statistical Analysis ◽  
Dna Sequences ◽  
Markov Chain Models

scholarly journals Proposal for Tower Crane Productivity Indicators Based on Data Analysis in the Era of Construction 4.0

Buildings ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 21
Author(s):  
Thomas Danel ◽  
Zoubeir Lafhaj ◽  
Anand Puppala ◽  
Sophie Lienard ◽  
Philippe Richard
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Statistical Analysis ◽  
Data Collection ◽  
Structural Phase ◽  
Sampling Technique ◽  
Construction Site ◽  
Data Logger ◽  
Tower Crane ◽  
Productivity Indicators

This article proposes a methodology to measure the productivity of a construction site through the analysis of tower crane data. These data were obtained from a data logger that records a time series of spatial and load data from the lifting machine during the structural phase of a construction project. The first step was data collection, followed by preparation, which consisted of formatting and cleaning the dataset. Then, a visualization step identified which data was the most meaningful for the practitioners. From that, the activity of the tower crane was measured by extracting effective lifting operations using the load signal essentially. Having used such a sampling technique allows statistical analysis on the duration, load, and curvilinear distance of every extracted lifting operation. The build statistical distribution and indicators were finally used to compare construction site productivity.

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