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Register a new userModeling the monthly flows of AL-SIN Spring in the Syrian Coast by using the time series analysis
نمذجة التدفقات الشهرية لنبع السن في الساحل السوري باستخدام تحليل السلاسل الزمنية
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تعتمد دراسة و تصميم المآخذ المائية للينابيع على تحليل السلاسل الزمنية للقياسات التاريخية من خلال التنبؤ بأحجام المياه الواردة أو المتوقع ورودها مستقبلاً. يهدف البحث إلى نمذجة تدفقات المياه الشهرية لنبع السن في الساحل السوري و التنبؤ المستقبلي بهذه التدفقات، باعتماد نماذج "بوكس– جنكنز" في تحليل بيانات السلسلة الزمنية، لارتفاع درجة الدقة في تنبؤاتها. اعتمدنا بيانات تدفقات المياه الشهرية و بالتالي حجوم المياه الشهرية لـ 101 شهراً من حزيران 2008 حتى تشرين الأول 2016م، و بعد إجراء عمليات استقرار السلسلة في التباين و المتوسط و إزالة الموسمية و تنفيذ الاختبارات المطلوبة على بواقي النموذج، تبيّن أن أفضل نموذج يمثل البيانات هو SARIMA(2,0,1) (2,1,0)12، و تم تقسيم البيانات إلى 81 شهراً لبناء النموذج و 20 شهراً لاختباره، و اعتماداً على أصغر قيمة للمتوسط الموزون للمعايير RMSE, MAP, MAE، فإن أفضل نموذج للتنبؤ هو النموذج SARIMA(3,1,0) (1,1,0)12، و قد أعطى النموذج تنبؤات قريبة من حجوم المياه الشهرية في النبع المقيسة فعلياً.
The study and design of water-intakes on springs is based on the analysis of time series of historical measurements to achieve prediction of incoming water volumes or future expected. The research aims to model the monthly water flows of AL-SIN Spring in Syrian Coast and future expectations of these flows, by adopting the Box-Jenkins models to analyze the time series data, due to its reliable accuracy. Monthly water flows, thus, monthly volumes, for 101 month (from June 2008 to October 2016) were processed. Performing the stability of the time series on variance and median and non-seasonality and making the wanted tests on model residuals, we found that the best model to represent the data is SARIMA(2,0,1) (2,1,0)12 , and after dividing the data into 81 month to build the model and 20 month to test it. Depending on the smallest of weighted mean of criteria RMSE, MAP, MAE,. The best predicted model was SARIMA (3,1,0) (1,1,0)12 and the model gave the nearest predicted values to actually measured data in spring.
References used
Springflow Simulator Manual Vers. 1.0.2, 2007. ACSAD-BGR TECHNICALCOOPERATION PROJECT - NO.: 2004.2032.3, Management, Protection and Sustainable Use of Groundwater and Soil Resources
NELSON, G. R., Applied Time Series Analysis For Managerial Forecasting, Holden- Day, Inc. 1973, 78-91
Box, G. M. P. and PIERCE, D. A., Distribution of Residual Autocorrelation in Autoregressive Integrated Moving Average Time Series Models, John Wiley & Sons. 1970, 115-132
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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.
AlSin Spring spurts at the foot of coastal mountains and pours in The Mediterranean sea
near Arab-Almulk village. Presently, spring water used for drinking, irrigation and
industry, while excess water goes to sea.
Current research aims to determin
e the daily discharge response to daily rainfall, and to set
an equation for recession discharge for predicting spring discharge and volumes of flow
after definite time from the beginning of spring base flow, which allows to operate and
manipulate available water resources through an optimum design of water intake from this
spring.
Response time of AlSin Spring between (3-5) days for average discrete daily rainfall with
high intensity which caused 0.5 ~ 1.0 m3/sec increasing in spring discharge value.
Yearly discharge trends to decrease with a rate of 0.0975 m3/sec between 1974 and 2016
years. While the monthly minimum discharges increase about 0.1284 m3/sec, and monthly
maximums decrease about 0.0752 m3/sec between 1994 and 2016.
We recommend adopting recession curve analysis to predict the optimal discharge of
springs within definite periods.
This study aimed to analyze the status of shares related to the
banking sector in Amman Stock Exchange, through the use of time series
analysis, relying on the achievement of the following objectives:
1- Analysis of the status of shares related to
the banking sector in
Amman Stock Exchange, through the use of time series analysis.
2- Access to an efficient market through the application of the
conditions existing in the market.
3- Analysis of the status of the general trend of stock prices in
Amman Stock Exchange, through the turnover rate of shares over
twelve months for eight years starting from 2000-2007 in order to
find the variables affecting performance.
4- Identifying the most important components of the time series
affecting stock prices in Amman Stock Exchange (seasonal,
periodical, and random), in addition to identifying which of these
components are responsible for stock price changes.
5- Trying to determine the general tendency of the time series of
stock prices for the coming period through the use of the model of
basic components.
This study was based on three major hypotheses. The study sample
consisted of the banks listed in Amman Stock Exchange with a total of 17
banks. Furthermore, Microsoft Office Excel had been used to analyze the
data of turnover rate of shares in Amman Stock Exchange to reach
conclusions.
The study came to a number of conclusions such as:
• Results showed that the influence of irregular variables on the
turnover rate of shares related to the banking sector, listed in
Amman Stock Exchange, was clear, in addition to the impact of
changes related to the general trend as well as the seasonal and
periodical changes.
• Results showed that the size of circulation plays a major role in
changing the direction of prices. Thus, in the case of higher prices,
increased circulation is desired, while decreased circulation will be
the case for low prices.
Based on the above conclusions, the researcher presented a series
of suitable recommendations for the use of analysis model of time series
in analyzing the status of shares in Amman Stock Exchange.
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 research area is located in the Syrian coast between the Sin and Rous river. This
research aims at studying the hydrogeological characteristics of the unconfined aquifer in
the research area and evaluating the conditions of its placed. The rese
arch was based on a
monitoring network consisting of 36 wells that penetrate the unconfined aquifer, and
measurements continued during the period (October 2016 until September 2017).
The unconfined groundwater depths in the research area range between 0.5-11.5 m, and
sometimes during the drought period reach to 13.5 m, while it is close to the surface in the
winter and up to 0.1m in some wells. The electrical conductivity ranges between
550-3700 μs/cm, increasing as we go west and reaching 9,000 μs/cm and more in the wells
near the sea during the dry period. Groundwater levels Lower in the dry period to below
sea level in near-shore wells, achieves the hydrodynamic conditions of the seawater
intrusion.
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