To solve this problem, a two-layer genetic algorithm–backpropagation (GA-BP) model is proposed. The algorithm focuses on multi-source data identification and fusion. Rainfall data from a sensor array ...

Small dataset: Consider a more complex model like Random Forest. Missing values: Opt for an algorithm robust to inconsistencies, like Decision Tree with Missing Value Handling. Labeled data ...

meaning it is the algorithms that turn a data set into a model. Which kind of algorithm works best (supervised, unsupervised, classification, regression, etc.) depends on the kind of problem you ...

This paper aims to study the data mining algorithm data model data analysis. First, this paper comprehensively expounds the basic theories and methods of data mining. On the basis of understanding and ...

Some algorithms used to identify outliers are: Time series modeling uses historical data to forecast events. A few of the common time series models are: ARIMA: The autoregressive integrated moving ...

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

This study proposes a method for simultaneously imaging multi-fracture networks using microseismic monitoring data. The random sample consensus and propose, expand, and re-estimate labels algorithms ...

The student is also exposed to the notion of a faster algorithm and asymptotic complexity through the O, big-Omega and big-Theta notations. In this module, the student will learn about the basics of ...