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Register a new userProposed method to analysis and predict time series with a regular cyclical factor (Olive production in Syria)
أسلوب مقترح للتنبؤ بالسلاسل الزمنية ذات الدور المنتظم (إنتاج الزيتون في سورية)
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تشهد زراعة الزيتون تطوراً ملحوظاً في الجمهورية العربية السورية من حيث المساحة المزروعة و عدد الأشجار و نوعية الأصناف المزروعة من الزيتون. نتيجة هذا التطور احتلت سورية المركز الأول في إنتاج الزيتون عربياً والمرتبة الخامسة عالمياً بعد إسبانيا وإيطاليا واليونان وتركيا متجاوزة تونس التي كانت تحتل المركز الأول عربياً. يتأثر إنتاج الزيتون كمتغير تابع بكثير من العوامل التي يمكن عدها مستقلة: و هي عدد الأشجار و عمر الشجرة و صنف الشجرة و كمية الأمطار و درجة الحرارة و مكان زراعة الزيتون....إلا أن أهم ما يؤثر في إنتاج الزيتون هو ظاهرة المعاومة. المعاومة أو تبادل الحمل الثمري alternate fruit bearing في الأشجار المثمرة. تؤدي ظاهرة المعاومة إلى تأثر سلسلة إنتاج الزيتون بعوامل دورية منتظمة فضلاً عن العوامل الأخرى، الاتجاه العام و العوامل العشوائية. هدفت هذه الدراسة إلى تقديم أسلوب جديد لنمذجة السلاسل الزمنية ذات الدور المنتظم و تحليلها و تطبيقها على إنتاج الزيتون في الجمهورية العربية السورية. خلصت الدراسة إلى وضع نموذج قياسي مبني على الأسلوب الجديد المقترح يمكن استخدامه في. التنبؤ بإنتاج الزيتون قي سورية، و قد قمنا بالتنبؤ بحجم الإنتاج حتى عام 2016.
Olive cultivation is witnessing a remarkable development in the Syrian Arab Republic in terms of area cultivated and the number of trees and the quality of cultivated varieties of olives. The result of this evolution Syria occupied first place in the Arab and olive production ranked fifth in the world after Spain, Italy, Greece and Turkey, by passing Tunisia, which occupies the first place was an Arab. Olive production as dependent variable is affected by much of the factors which can be considered independent: The number of trees and age of tree and tree type and amount of rainfall, temperature and location of olive cultivation…… However, the most important influence on the production of olive is a phenomenon alternate fruit bearing in fruit trees.This lead to the affected by a time series of olive production, in addition to the regular periodic of other factors, the general trend and random factors. This study aims to provide a new method for modeling and analysis of time series with a regular cyclical factors and its application to olive production in the Syrian Arab Republic. The study to develop an econometric model based on the proposed new method can be used to predict the production of olive in Syria, and predict the size of production until 2016. ...
References used
Baltagi B.H. (2008) "Econometrics". Springer-Verlag Berlin
BARDSEN G. and others (2005) " the econometrics of macroeconomic modelling". Oxford University Press Inc., New York
BARRETO H. and HOWLAND F.M. (2006) "INTRODUCTORY ECONOMETRICS". cambridge university press
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The study aims at comparing ARIMA models and the exponential
smoothing method in forecasting. This study also highlights the special
and basic concepts of ARIMA model and the exponential smoothing
method.
The comparison focuses on the ability
of both methods to forecast
the time series with a narrow range of one point to another and the time
series with a long range of one point to another, and also on the different
lengths of the forecasting periods. Currency exchange rates of Shekel to
American dollar were used to make this comparison in the period
between 25/1/2010 to 22/10/2016. In addition, weekly gold prices were
considered in the period between 10/1/2010 to 23/10/2016. RMSE
standard was used in order to compare between both methods. In this
study, the researcher came up with the conclusion that ARIMA models
give a better forecasting for the time series with a long range of one point
to another and for long term forecasting, but cannot produce a better
forecasting for time series with a narrow range of one point to another as
in currency exchange prices.
On the contrary, exponential smoothing method can give better
forecasting for Exchange Rates that has a narrow range of one point to
another for its time series, while it cannot give better forecasting for long
term forecasting periods
The main objective of this research was the reality of irrigated olive
cultivation and analysis of production costs in the eastern region of the
province of Homs and identify the most important influence on profit
productive elements, The initial
field data collection of 2014 and 2015.
حظيت نمذجة وتوقع السلاسل الزمنية بأهمية كبيرة في العديد من المجالات التطبيقية كالتنبؤ بالطقس وأسعار العملات ومعدلات استهلاك الوقود والكهرباء، إن توقع السلاسل الزمنية من شأنه أن يزود المنظمات والشركات بالمعلومات الضرورية لاتخاذ القرارات الهامة، وبسبب
أهمية هذا المجال من الناحية التطبيقية فإن الكثير من الأعمال البحثية التي جرت ضمنه خلال السنوات الماضية، إضافةً إلى العدد الكبير من النماذج والخوارزميات التي تم اقتراحها في أدب البحث العلمي والتي كان هدفها تحسين كل من الدقة والكفاءة في نمذجة وتوقع السلاسل الزمنية.
The study and design of water dams depend essential on prediction of water volumes
or future predicted in rivers, by using the time series analysis of the historical
measurements.
The research aims to make statistical study of monthly water volume
s incoming in
AL-Aroos River in Syrian coastal and future prediction of these volumes. And the
Box-Jenkins models is adopt to analysis the time series data, because of its high accuracy.
We attend the monthly water volumes for 15 years. And after doing the wanted tests on
model residuals we found that the best model to represent the data is SARIMA(0,1,2)
(1,2,1)12 , and after dividing the data to 14 years to build the model and one year to test it ,
and depending on the smallest of weighted mean of criteria RMSE, MAP, MAE,. The best
predicted model is SARIMA (1,1,0) (0,1,1)12 and the model give the nearest predicted of
measured data actually.
The analysis of time series data is one of the most important statistical
topics, usually focuses on forecasting the future behavior of the series at a
certain time for certain purposes.
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