English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Our society is increasingly influenced by modern information and communication technology (ICT), Data warehouse, data mining and time series data mining etc. Time series data mining can be treated as a subset of data mining domain. The nature of time series data is large data size, high dimensionality and necessary to update continuously. Time series data mining (TSDM) is a rapidly evolving research area in Computer Science. While processing data stored in a data base, if we consider the time at which the event happened, the information technology professional can generate more reliable and dependable information in comparison with conventional methods. Potentially, today, every stake holders has got the opportunity for time series data mining. In this paper I am introducing a methodology and a strategy for the effective planning of various organizational resources for different stake holders in the form of cases. Few of them are Information Technology professionals planning their hardware, software and network (bandwidth) requirement for the organizations. Another category of user is top level business executives, they are responsible for the long term strategic decision making of their business. The next category of users I am planing to cover in this paper is medical professionals or biological researchers and share traders (equity market).

Time Series Data Analysis For Long Term Forecasting and Scheduling of Organizational Resources Few Cases