分析結果顯示利用年度的預測來比較月份預測的話，會發現冬季的1、2月的正

分析結果顯示利用年度的預測來比較月份預測的話，會發現冬季的1、2月的正確率低於年度預測，為此可以說明1.2月番茄市場是不穩定的，則12月卻跟年度的預測
是差不多的，代表著冬季的預測率不高是被1.2月所以影響。
春季代表月份3.4.5月則是一年中在番茄市場最不穩定的時間，從上表可以看出不止預測命中率不高，正確率相較於其他預測只接近於8成，這代表著一年之中這些月份在番茄在市場上是最容易受到外在因素影響市場價格導致成交量不規律、不穩定。
一年中預測正確率最高的是在8.9.10月部份，從這3個月原始數據中，發現到因為這3個月的成交量是屬於第1類的，這意味著這3個月的成交量是最低的，因此我們可以猜測，這時是番茄非產季，才可能導致這時的分類是最低，也最不容易被外在因素影響市場價格與成交量。

ผลลัพธ์ (อังกฤษ) 1:

Fruit 顯 follows annual analysis be used to predict measured comparison month predict measured said in the future, it'll happen now winter December is true low plasticity of the year measured, because this can explain the tomato market is 1.2 months not 穩, entering into December, but the annual predict measuredIs about the same, representing the plasticity of measured rate is not high enough in the winter flowinfluence by 1.2 months. Spring representative month 3.4.5 months entering into is a years in the in tomato city Gatwick most not 穩 set of when between, promote Shang table can see more than plasticity measured hits not high, are true rate phase 較 in other plasticity measured only close in 80%, this representative with a years among this some month in tomato in city Gatwick Shang is most easy by external factors shadow 響 city Gatwick price grid 導 to volume not rules law, and not 穩 set. A years in the plasticity measured are true rate highest of is in 8.9.10 months part, promote this 3 real months original number high speed circuit switched data in the, release now to for because this 3 real months of volume is're part in 1th class of, this means with this 3 real months of volume is minimum of, so I we can guess measured, this when is tomato non-production quarter, only may 導 to this when of points class is minimum, also most not easy was external factors shadow 響 city Gatwick price grid stub volume.

ผลลัพธ์ (อังกฤษ) 2:

The results show to compare the month of the year with the predicted forecast, you will find the winter in January and February was lower than the annual forecast is correct, for which you can Note 1. February tomato market is unstable, however, predicted that with the December year
is about the same, representing winter forecast rate is not high by 1, so the impact in February.
3.4 in the spring for the month of May in the year tomato market is the most volatile time, it can be seen from the table more than forecast hit rate is not high, compared to other predictive accuracy only near 8 percent, which represents The month of the year on the market in tomatoes are the most vulnerable to external factors influencing the market prices led to turnover irregular and unstable.
Year forecast accuracy rate is the highest in 8.9 October part, from three months of the original data, we found that the lack of this three-month trading volume is part of Class 1, which means that three months The volume is the lowest, so we can guess, when the non-production of tomato season, it may result in the lowest classification at this time, but also the least likely to be affected by external factors, the market price and trading volume.

ผลลัพธ์ (อังกฤษ) 3:

The analysis results show that the forecast of the year will be more than the forecast of winter, and the correct rate is lower than that of the annual forecast. For this purpose, the tomato market in 1.2 months is not stable, but the forecast of December is almost the same as that of the year, which means that the forecast rate is 1.2 months. 3.4.5 month in spring is the most unstable time in the tomato market in a year, and from the above table, it can be seen that the accuracy rate is not high, and the correct rate is close to 8,This represents the year of these months in the tomato market is the most vulnerable to external factors affecting the market price of the market price is not stable. The highest prediction accuracy of the year is in the 8.9.10 months, from the 3 months of the original data, found that the volume of the 3 months is belong to the first category, which means that the turnover is the lowest in 3 months, so we can guess, this is the tomato production season, it may lead to the classification is the lowest, it is not easy to be external factors affecting market prices and trading volume.