1、能源資源中英文對照外文翻譯文獻能源資源中英文對照外文翻譯文獻(文檔含英文原文和中文翻譯)土耳其的能源需求摘要：本研究的目的是預測在土耳其使用 Box-Jenkins方法論 2007 - 2015 1970至 2006年的年度平穩。位居其后的替代模型可以發現，最合適的模型是能源需求的系列 ARIMA（3,1,3測期內。據預計，在一次能源需求將在 2015年達到 119.472 TOE與相比，應設計用于在土耳其的需求不斷增加 2006.因此能源政策增加約 22。源，以實現在社會福利的增加，以增加產量。出于這個原因，可以看出，已內化能源資源中英文對照外文翻譯文獻 18 世紀末和 19 提到的局限性迫

2、使國家在考慮到可持續增長做出預測已經塑造他們的能源政策。本研究的目的是預測在土耳其通過 Box-Jenkins 方法的基礎上規定的期限 1970年至 2006 年的年度數據對能源的需求期間二零零七年至 2015 認為是豐富的化石燃料，諸如石油，天然氣和煤炭的國家之列。出于這個原因，正確的能量需求預測攜帶在設計在國內實施的策略一個顯著值。能源資源，另一方面，他們專注于項目，將提供更有效和高效地利用現有資源（DPT1996素，如工業化，人口和城市化在世界各地。實際上，因為它可以在圖 1 中所示，全球能源消耗，這是283.3 萬億英熱單位（英國熱量單位（BTU 63 F 加熱一磅水（453.6 克）

3、至64F.所需的能源量）在1980 年，達到472.5 萬億英熱單位在 2006 年同比增長約 66.8左右。它還預測，該值將在 2030 年達到 678.3萬億英熱單位（EIA，2006）天然氣和煤，核能和可再生能源資源滿足。據預測，汽油，天然氣和煤，這是最2 中顯示，其中在根據資源的全球能源消費的發展等，并針對它吸引注意，可再生能源如陽光，風，水和地熱資源將在未來變得更為重要（EIA，2006）在社會經濟平衡尤其是 1980 年以后的變化有這種傾向顯著的貢獻。因此，在第4 個計劃期間，包括1983 年 1978，一次能源消費不能超過由于發生在上世紀70能源資源中英文對照外文翻譯文獻年代的經

4、濟，政治和社會不穩定2.1的年。在20世紀 80年代后半期，隨著經濟觀察復蘇持續的城市化進程共同造成能耗增加至 6 20世紀 90年代平均為4.3。 6.1年均增長在 8日計劃期間并行與旨在要達到的經濟增長率目標。目標數目 2003中，其中，經濟獲得穩定和2001DPT2006年）的影響后達到在周期一定程度。圖 3部預測，能源需求將達到約 1.7億 TOE 4增長約 60對能源生產和消費目前的情況。的水平，觀察到預測的結果通常彼此不同。Ediger和 Akar（2007 ARIMA和季節性 ARIMA方法的期間 2005-2020。該研究得到的結果表明，在每年的能源需求，這是在1950-200

5、5 年期間 4.9的增長速度，將下滑至 3.3在 2005-2020 年期間，Unler（2008年）所使用的粒子群優化（PSO）技術來預測 2006-2025的基礎上在 1979-2005年期間獲得的數據期間的能源需求。 Ediger和 Tatl1dil（2002）預測，通過使用周期分析方法根據從周期 1950-1999的數據的主要的能源需求。他們在研究中取得的成果表明，能源需求總量將在 2010年達到阿凱 131440000TOE2007 1970年至 2004年期間的數據預測工業和全社會用電量的未來值。這是通過使用 GPRM方法預測調查結果顯示，工業能耗將達到 140.37 2015年

6、2Toksar（2009 265.7雷公藤預測期間 2007年至 2025ACO）根據不同的 GDP，人口和進口增長率的情況。 2007年）通過“人工ANN）預測的2003-2020期間用電能耗。根據能量需求分析模型，所能源資源中英文對照外文翻譯文獻部門預測較高和較低。 Erdogdu（2007）提供了用于基于通過使用協整分析和ARIMA模型通過1923年至2004年期間的數據對2005-2014期間預測的電力需求。他的研究結果提出的用電量將在 2015年達到 160.090億千瓦時，呈現出 3.3Erdogdu（2009 ARIMA模型周期 1987- 2007年分析的數據和計算的天然氣消費

7、量將達到 2008年期間的值-2030 1關于在土耳其能源需求預測進行的研究信息。能源資源中英文對照外文翻譯文獻與此研究中，它的目的是預測在土耳其使用 Box-Jenkins 方法論的期間2007-2015 的初級能源需求。為此，由能源和自然資源部規定的期限 1970 年至2006 年的年度數據預測研究中的能源需求作為依據。Box-Jenkins Box-Jenkins 的方法被廣泛認為 ARIMA ARIMABaltagi2008ARIMA 方法結合兩個不同的部分為一個方程;它們是自回歸過程和移動平均處理（Bashier 和塔拉勒，2007AR）是其中變量（YT）的當前值是它的過去值的函數加

8、上一個誤差項;如：YT p u 是誤差項和正態分布的。的 AR 過程可以寫成滯后算形式：移動平均處理假定變量 YT 的當前值作為誤差項加一恒定的過去的值的函能源資源中英文對照外文翻譯文獻數。順序（Q）移動平均線，MAX（Q）表示為：主要過程可寫成滯后算法形式：創建 ARIMA模型，可以把兩個規范沒有獨立變量組合成一個方程式，如下：其中， ，是 ARIMA系數分別。在滯后算法組成的 ARIMA模型如下：一個 ARIMA模型（肯尼迪，2003年）建立的三個基本步驟：（1）識別/模型選擇：P、D和 q的值必須被確定。簡約的原則，采用最平穩時間序列可使用 p和 q的非常低的值進行建模。（2）估計： 和

9、參數必須估計，通常是通過使用最小二乘近似最大似然估計。（3）診斷檢查：估計模型必須檢查其是否足夠，如果需要修訂，這意味著這整個過程可能要重復進行，直到一個滿意的模型中找到。為了通過使用盒 - 詹金斯方法來執行預測中，首先，該系列的平穩性，通過使用自相關函數（ADF）和 Dickey-Fuller（ADF）的試驗進行測試。根據表 2中所示的原始序列的相關圖中，自相關和部分自相關值落在 95的 ADF檢驗統計比 MacKinno臨界值中的 1，5和 10的顯著性水平的絕對值越大支持該結果（表 3能源資源中英文對照外文翻譯文獻為此，它被認為在固定的水平，一階差的相關性如圖4和表 4，作為自相關和部分

10、自相關值落入 95%差差異的平穩狀態。 ARIMA模型用于通過盒式詹金斯方法預測通過使用序列、 Akaike 和 Schwarz 標準的一階差值獲得的相關性鑒定為 ARIMA（3,1,3 5中給出。一系列的殘差的相關圖進行了檢查（表 6該殘差的 ACF和 PACF是 95自相關通過使用 Breusch-GodfreyLM檢驗也進行測試。結果進行了檢查最多 10滯后和可看出，沒有了任何自相關，如概率值被發現是 0.05（表 7）更大。測試該模型的相關性之后，使初級能源需求將在 2007-2015年期間顯示趨 5 97.995TOE在 2006年，將通過在 22的速度增加，2015年達到 119.

11、472 TOE。還有在本研究中取得的成果和能源和自然資源部的官方預測之間差異顯著。我們在看表8所示為201548.331TOE。但是，在由Ediger和 （2007）進行的研究中獲得的預測結果是顯著類似于在本研究中所獲得的預測結果。能源資源中英文對照外文翻譯文獻能源資源中英文對照外文翻譯文獻的因素，如工業化，人口和城市化在世界各地迅速增加的趨勢。據預測，汽油，天然氣和煤，這是最消耗這些資源，將保持在未來的重要性。同樣，在土耳其能耗也趨于迅速增加。能源和自然資源部預測，能源需求將增加 60左右的情況下，目前的情況。而能源需求 97.995 TOE于 2006年，據估計，能源需求將在2015年達到

12、 170.154 TOE在本研究的基礎上，這一期間的年度數據的一次能源需求的未來價值進行了預測土耳其 1970-2006年通過 Box-Jenkins自相關函數（ACF）和增廣迪基-富勒（ADF）的測試用于測試的能量需求系列平穩性。位居其后的替代機型可以發現，最合適的模型是能源需求的系列 ARIMA（3,1,3 ARIMA影于本期間取得 2015 年 2007-研究中獲得的發現表明，一次能源需求，這是97.995TOE2006年，將通過在 22的速度增加，2015年達到 119.472TOE。雖然這些結果都低于能源和自然資源部的官方預測，它們類似于 Ediger 和 Akar（2007年）的預

13、測。Akay, D. and M. Atak, 2007. Grey prediction with rolling mechanism for electricitydemand forecasting of Turkey. Energy, 32: 1670-1675.能源資源中英文對照外文翻譯文獻Baltagi, B.H., 2008. Econometrics, 4th Edn., Springer, Berlin.Bashier, A. and B. Talal, 2007. Forecasting foreign direct investment inflow in Jordan:

14、Univariate ARIMA model. J. Soc. Sci., 3(1): 1-6.DPT, 2006. Dokuzuncu Kalk 2 nma Plan 2 (2007-2013). Devlet Planlama Teskilat1,Ankara.DPT, 1996. Petrol-Dogal Gaz, Madencilik zel htisas Komisyonu EnerjiHammaddeleri Alt Komisyonu Petrol ve Dogal Gaz algma Grubu Raporu. DevletPlanlama Tegkilat Ankara.Ed

15、iger, S. and S. Akar, 2007. ARIMA forecasting of primary energy demand byfuel in Turkey. Energy Policy, 35: 1701-1708.Ediger, S. and H. Tatl 2 dil, 2002. Forecasting the primary energy demand inTurkey and analysis of cyclic patterns. Energ. Convers. Manage., 43: 473-487.EIA, 2006. Energy Information

16、 Administration, International Energy Annual 2006.Erdogdu, E., 2009. Natural gas demand in Turkey. Appl. Energ., 87: 211-219.Erdogdu, E., 2007. Electricity demand analysis using cointegration and ARIMAmodelling: A case study of Turkey. Energ. Policy, 35: 1129-1146.Erdogdu, E., 2007. Electricity dema

17、nd analysis using cointegration and ARIMAmodelling: A case study of Turkey. Energ. Policy, 35: 1129-1146.Hamzaebi, C., 2007. Forecasting of Turkeys net electricity energy consumption onsectoral bases. Energ. Policy 35: 2009-2016.Kennedy, P., 2003. A Guide to Econometrics, 5th Edn., MIT Press, Bodmin

18、.Toksar1, M.D., 2009. Estimating the net electricity energy generation and demandusing the ant colony optimization approach: Case of Turkey. Energy Policy 37:1181-1187.nler, A., 2008. Improvement of energy demand forecasts using swarm intelligence:The case of Turkey with projections to 2025. Energ.

19、Policy 36: 1937-1944.建模方法和實現過程能源資源中英文對照外文翻譯文獻則選定該模型。圖 1 概括了自回歸求和滑動平均法的建模流程。ARIMA 建模包含以下基本步驟:模型識別，參數估計，模型檢驗和模型預測。1 模型識別ARIMA 著考察其自相關函數與偏自相關函數，爾后進行初步識別:若平穩時間序列的偏自相關函數是截尾的，而自相關函數是拖尾的，則可斷定此序列適合 AR 模型;列適合 MA 模型;序列適合 ARIMA 模型。2 參數估計 F 低階到高階擬合 ARIMA 數的估計方法有多種，其中有效方法為最小二乘估計大洪和機女似然估計方俠。3 模型檢驗i)說明試用模型是適合的;否則試

20、用模型尚需進一步改進。4 模型預測行預測;隨著分析數據的增多，同一 ARIMA 模型能校正為適合另一段時間里的預能源資源中英文對照外文翻譯文獻參數.若有必要需重新建模。Turkeys Energy DemandM. Mucuk and D. UysalDepartment of Economics, Selcuk University Faculty of Economics and AdministrativeSciences,42075, Konya, TurkeyAbstract:The present study aims to forecast the primary energy

21、demand in Turkeyfor the period 2007-2015 using the Box-Jenkins methodology. The annual data forthe period 1970-2006 provided by the Ministry of Energy and Natural Resources wereused in the study. Considering the results of unit root test, energy demand series isstationary at first difference. Later

22、among alternative models it is found that the mostappropriate model is ARIMA (3,1,3) for energy demand series. According to thismodel, estimation findings show that the energy demand would continue itsincreasing trend also in the forecast period. It is expected that the primary energydemand will rea

23、ch 119.472 TOE in 2015 with an approximately 22 percent increasecompared to 2006. Therefore energy policies should be designed for increasingdemand in Turkey.INTRODUCTIONThe ultimate objective of economic policies is to maintain an increase in the level ofsocial welfare. It is necessary to increase

24、production by using the resourceseffectively and efficiently in order to achieve an increase in social welfare. For thisreason, it can be seen that the technology factor which has been internalized intonew growth models is in a rapid development. The developments in technology alsocontribute to the

25、increase in the demand for energy. In fact, the use of newtechnologies in the production process with the Industrial Revolution, which tookplace in the late 18 century and the beginning of the 19 century, brought along anththincrease in energy consumption both on country basis and on a global scale.

26、 However,together with industrialization, factors such as population and urbanization have alsoplayed a significant role as explanatory variables for the increase in energyconsumption. The future values of energy demand, which exhibits a dynamicstructure depending on the factors mentioned above, are

27、 of great importance interms of the policies that are to be implemented today, because the energyresources that are used the most in our day have an unbalanced distribution amongthe regions and the reserves have been decreasing steadily. The limitationsmentioned above force the countries to already

28、shape their energy policies by takinginto consideration the forecasts made for sustainable growth. The present study aimsto forecast the energy demand in Turkey for the period 2007-2015 through theBox-Jenkins methodology based on the annual data provided for the period1970-2006.Turkey is not listed

29、among the countries that are considered to be rich in能源資源中英文對照外文翻譯文獻terms of fossil fuels such as petrol, natural gas and coal. For this reason, correctenergy demand forecasts carry a significant value in designing the policies to beimplemented in the country.Energy Demand in Turkey and in the World

30、: In order to meet the energy demand,countries on the one hand continue their search for new energy resources and on theother hand, they focus on projects which will provide more effective and efficient useof existing resources (DPT, 1996). The reason for this search is that energyconsumption shows

31、a tendency to increase rapidly depending on factors such asindustrialization, population and urbanization throughout the world. In fact, as it canbe shown in Fig. 1, the global energy consumption, which was 283.3 quadrillion Btu(British Thermal Unit (Btu), the amount of energy needed to heat one pou

32、nd (453.6 g)of water from 63 F to 64 F.) in 1980, reached 472.5 quadrillion Btu in 2006 with anincrease of approximately 66.8 percent. It is also predicted that this value will reach678.3 quadrillion Btu in 2030 (EIA, 2006)The demand for energy, which shows a tendency to continuously increase over t

33、ime,is currently met through fossil fuels such as petrol, natural gas and coal and nuclearand renewable energy resources. It is forecasted that petrol, natural gas and coal,which are the most consumed of these resources, will maintain their importance alsoin the future. However, the decrease in the

34、reserves of the mentioned resources asthe result of the increase in consumption at the same time leads the consumerstowards alternative energy resources. This situation can apparently be shown in Fig.2, where the developments in the global energy consumption according to resourcesare presented, and

35、it attracts attention that renewable energy resources such assunlight, wind, water and geothermal resources will become more important in thefuture (EIA, 2006)Energy consumption in Turkey also shows a tendency to increase rapidly in parallelwith the developments throughout the world. The changes tha

36、t occurred in socio-economic balances especially after 1980 have a significant contribution to thistendency. Consequently, during the 4th Plan period comprising the years 1978- 1983,the primary energy consumption could not exceed 2.1 percent due to the economic,political and social instabilities tha

37、t occurred in the 1970s. In the second half of the1980s, the continuing urbanization process together with the recovery observed inthe economy caused a rise in the annual average rate of increase of energyconsumption to 6 percent. This rate decreased to an average of 4.3 percent in the1990s when the

38、 negative effects of the economic crises were clearly felt. An annualaverage increase of 6.1 was targeted during the 8 Plan period in parallel with thetheconomic growth rate that was aimed to be achieved. The targeted number wasachieved to a certain extent in the period after 2003, where economy gai

39、ned stabilityand the effects of the 2001 crisis subsided (DPT, 2006).Fig. 3 shows that energy consumption shows an increasing trend depending onfactors such as population, urbanization and industrialization. The graph also drawsattention to the fact that although certain breaks were observed in the

40、periods wheneconomic crises occurred and their effects continued, the general tendency of energy能源資源中英文對照外文翻譯文獻consumption to increase did not change. The Ministry of Energy and NaturalResources forecasts that the energy demand will reach approximately 170 millionTOE (Tons of Oil Equivalent), with a

41、n increase of approximately 60 percent in case thepresent situation regarding energy production and consumption continues (Fig. 4).In Turkey, there are several forecasting studies regarding the future energyconsumption conducted by using different methods and taking different periods intoconsiderati

42、on. In these studies, although it was forecasted that the energy demandwould increase in time and reach significant levels, it is observed that the results ofthe forecasts were generally different from each other.Literature Review: There are several studies on energy demand forecasting in Turkey.Of

43、these studies, Ediger and Akar (2007) forecasted the primary energy demand withrespect to types of fuel for the period 2005-2020 by using the ARIMA and theseasonal ARIMA methods. The results obtained in the study showed that the rate ofincrease in the annual energy demand, which was 4.9 percent in t

44、he period1950-2005, would fall to 3.3 percent in the period 2005-2020. Unler (2008) used theParticle Swarm Optimization (PSO) technique to forecast the energy demand for theperiod of 2006-2025 based on the data obtained in the period 1979-2005. Ediger andTatl1dil (2002) forecasted the primary energy

45、 demand based on the data from theperiod 1950-1999 by using the cycle analysis method. The results they obtained inthe study showed that the total amount of energy demand would reach 131.44million TOE in 2010. Akay and Akat (2007) forecasted the future values of industrialand total electricity consu

46、mption by using the data concerning the period between1970 and 2004. The findings that were forecasted by using the GPRM approachshowed that the industrial energy consumption would reach 140.37 TWH and thetotal energy consumption would reach 265.7 TWH in 2015. Toksar 2 (2009)forecasted the electrici

47、ty demand for the period 2007-2025 under three scenariosbased on different GDP, population and import growth rates by using ant colonyoptimization (ACO). Hamzaebi (2007) forecasted the electricity energy consumptionfor the period 2003-2020 by using “artificial neural networks” (ANN). According tothe

48、 energy demand analysis model, the findings of the artificial neural networksstudy showed that the level of consumption would be realized higher than predictedin the housing and agricultural sectors and lower in industry and transportation.Erdogdu (2007) provided an electricity demand forecast for t

49、he period 2005-2014based on the data from the period 1923-2004 by using cointegration analysis andARIMA modeling. The results of his study presented that electricity consumption willreach 160.090 GWh in 2015, showing an annual average increase of 3.3 percent. Inhis study on natural gas demand, an is

50、sue which has recently come into prominencein Turkey,Erdogdu (2009) analyzed the data from the period 1987- 2007 using anARIMA modeling and calculated the values that natural gas consumption would reachin the period 2008-2030. Information regarding the studies conducted on energydemand forecasting i

51、n Turkey is shown in Table 1.能源資源中英文對照外文翻譯文獻能源資源中英文對照外文翻譯文獻MATERIALS AND METHODSWith this study, it is aimed to forecast the primary energy demand in Turkey for theperiod 2007-2015 using the Box-Jenkins methodology. For this purpose, the annualdata for the period 1970-2006 provided by the Ministry o

52、f Energy and NaturalResources were used as basis in forecasting the energy demand in the study.Box-Jenkins Methodology: The Box-Jenkins methodology used in analysis andforecasting is widely regarded to be the most efficient forecasting technique. Thismethodology fits Autoregressive Integrated Moving

53、 Average (ARIMA) type models(Baltagi, 2008). ARIMA approach combines two different parts into one equation;they are the Autoregressive process and Moving average process (Bashier and Talal,2007). The autoregressive process (AR) is one where the current value of the variable(Yt) is a function of its

54、past values plus an error term; as in:where Yt is the variable is being forecasted, p is the number of the past values usedand u is the error term and normally distributed. The AR process can be written in lagoperator form as:A moving average process assumes the current value of the variable Yt as a

55、 functionof the past values of the error term plus a constant. A moving average of order (q),MA (q) is expressed as:The MA process can be written in lag operator form as:To create an ARIMA model, one begins by combining the two specifications into oneequation with no independent variable, as follows

56、:能源資源中英文對照外文翻譯文獻Where and are the coefficients of the ARIMA respectively. In lag operatorform the ARIMA model can be as follows:There are three basic steps to the development of an ARIMA model (Kennedy, 2003):Identification / model selection: The values of p, d, and q must be determined. Theprincipl

57、e of parsimony is adopted; most stationary time series can be modeled usingvery low values of p and q.Estimation: The andparameters must be estimated, usually by employing a leastsquares approximation to the maximum likelihood estimator.Diagnostic checking: The estimated model must be checked for it

58、s adequacy andrevised if necessary, implying that this entire process may have to be repeated until asatisfactory model is found.RESULTSIn order to perform forecasting by using the Box- Jenkins methodology, first, thestationarity of the series was tested by using the autocorrelation function (ACF) a

59、ndthe Augmented Dickey-Fuller (ADF) tests.According to the correlogram of the original series shown in Table 2, theautocorrelation and partial autocorrelation values fall outside the confidence limit of95% with a certain level of lag. This shows that energy demand has a unit root at thelevel. That t

60、he calculated ADF test statistics are larger than the absolute value of theMacKinnon critical values at the 1%, 5% and 10% significance levels supports thisresult (Table 3).The correlogram obtained for the first difference of the series, which was found to bestationary at the level, is shown in Tabl