Architectural Representation for Inference rules generation for Astrological Predictions using induction of Horoscope Charts

摘要

Astrology not only specifies the future prediction, but also the past activities happened in our life. Astrology is the subset of Astronomy which represents our Galaxy system. Although saying that Astrology had 40 Decades of age, its origin was in Krutayuga. Horoscope chart is an Astrological representation that contains the movement of Nine planets (Navagrahas) located in twelve houses (Rashis) with periodic positional movements. In Horoscope representation some houses might be empty and others contain one or more planets. Horoscope comprises of various charts such as Lagna, Amsha, Bhava and so on and by using these charts we can predict in various ways. Assumption that any astrological prediction is about 70% of accuracy, but the number of believers increasing as well as with proportionate rejectors. Artificial Intelligence is an interdisciplinary domain, most widely using in various fields. It is also very useful to develop inference engine for Astrological predictions. The current paper specifies the Architectural overview for Astrological Inference engine that uses person's Date of Birth using Horoscope Charts. Because of Astrology is having vast scope and so predictions happened in various aspects such as studies, profession, colour complexion, assets and liabilities, marriage and so on. Methodologies such as zeroR, Simple Cart, Decision Table, Case Based Reasoning were used to evaluate some scope. Machine Learning algorithms such as Support Vector machines, Linear Regression, Logistic Regression and so on are useful to compute the Astrological predictions. Using Astrology, country's growth also be predicted using current positioning of Nine Planets. Training and Test sets are going to be used in designing inference rules. Predictive Modelling is the centre to evaluate inferences.