Travel-time Prediction Using K-nearest Neighbor Method with Distance Metric of Correlation Coefficient
نویسندگان
چکیده
منابع مشابه
Drought Monitoring and Prediction using K-Nearest Neighbor Algorithm
Drought is a climate phenomenon which might occur in any climate condition and all regions on the earth. Effective drought management depends on the application of appropriate drought indices. Drought indices are variables which are used to detect and characterize drought conditions. In this study, it was tried to predict drought occurrence, based on the standard precipitation index (SPI), usin...
متن کاملLiquid-liquid equilibrium data prediction using large margin nearest neighbor
Guanidine hydrochloride has been widely used in the initial recovery steps of active protein from the inclusion bodies in aqueous two-phase system (ATPS). The knowledge of the guanidine hydrochloride effects on the liquid-liquid equilibrium (LLE) phase diagram behavior is still inadequate and no comprehensive theory exists for the prediction of the experimental trends. Therefore the effect the ...
متن کاملStock Price Prediction Using K-Nearest Neighbor (kNN) Algorithm
Stock prices prediction is interesting and challenging research topic. Developed countries' economies are measured according to their power economy. Currently, stock markets are considered to be an illustrious trading field because in many cases it gives easy profits with low risk rate of return. Stock market with its huge and dynamic information sources is considered as a suitable environment ...
متن کاملAir Quality Index Prediction using K-Nearest Neighbor Technique
One of the classical data mining techniques is k-nearest neighbor. This method uses the class of the k nearest neighbor to classify a new instance. The distance is calculated with one of the multiple mathematical distance metrics. In this paper, the technique is used in the air quality forecast domain in order to predict the value of the air quality index. This index is used to categorize the p...
متن کاملPractical Construction of k-Nearest Neighbor Graphs in Metric Spaces
Let U be a set of elements and d a distance function defined among them. Let NNk(u) be the k elements in U−{u} having the smallest distance to u. The k-nearest neighbor graph (knng) is a weighted directed graph G(U, E) such that E = {(u, v), v ∈ NNk(u)}. Several knng construction algorithms are known, but they are not suitable to general metric spaces. We present a general methodology to constr...
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: The Open Transportation Journal
سال: 2019
ISSN: 1874-4478
DOI: 10.2174/1874447801913010141