Predicting individual phenological phases in peaches using meteorological data
نویسندگان
چکیده
منابع مشابه
Predicting Joint Choice Using Individual Data
Choice decisions in the marketplace are often made by a collection of individuals or a group. Examples include purchase decisions involving families and organizations. A particularly unique aspect of a joint choice is that the group’s preference is very likely to diverge from preferences of the individuals that constitute the group. For a marketing researcher, the biggest hurdle in measuring gr...
متن کاملpattern recognition in maintenance data using methodologies data minitng (cade study isfahan regional power electric company)
فعالیت های نگهداری و تعمیرات اطلاعاتی را تولید می کند که می تواند در تعیین زمان های بیکاری و ارایه یک برنامه زمان بندی شده یا تعیین هشدارهای خرابی به پرسنل نگهداری و تعمیرات کمک کند. وقتی که مقدار داده های تولید شده زیاد باشند، فهم بین متغیرها بسیار مشکل می شوند. این پایان نامه به کاربردی از داده کاوی برای کاوش پایگاه های داده چندبعدی در حوزه نگهداری و تعمیرات، برای پیدا کردن خرابی هایی که موجب...
15 صفحه اولPredicting phenological shifts in a changing climate.
Phenological shifts constitute one of the clearest manifestations of climate warming. Advanced emergence is widely reported in high-latitude ectotherms, but a significant number of species exhibit delayed, or no change in, emergence. Here we present a mechanistic theoretical framework that reconciles these disparate observations and predicts population-level phenological patterns based solely o...
متن کاملMeteorological Data Analysis Using MapReduce
In the atmospheric science, the scale of meteorological data is massive and growing rapidly. K-means is a fast and available cluster algorithm which has been used in many fields. However, for the large-scale meteorological data, the traditional K-means algorithm is not capable enough to satisfy the actual application needs efficiently. This paper proposes an improved MK-means algorithm (MK-mean...
متن کاملpredicting dryland wheat yield from meteorological data using expert system, khorasan province, iran
khorasan province is one of the most important provinces of iran, especially as regards agricultural products. the prediction of crop yield with available data has important effects on socio-economic and political decisions at the regional scale. this study shows the ability of artificial neural network (ann) technology and adaptive neuro-fuzzy inference systems (anfis) for the prediction o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Horticultural Science
سال: 2008
ISSN: 0862-867X,1805-9333
DOI: 10.17221/640-hortsci