Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Modern time-domain astronomy is capable of collecting a staggeringly large amount of data on millions of objects in real time. This makes it almost impossible for objects to be identified manually. Therefore the production of methods and systems for the automated classification of time-domain astro-nomical objects is of great importance. The Liverpool Telescope has a number of wide-field image gathering instruments mounted upon its structure. These in-struments have been in operation since March 2009 gathering data of multi-degree sized areas of sky around the current field of view of the main telescope. Utilizing a Structured Query Language database established by a pre-processing operation upon the resultant images, which has identified millions of candidate variable stars with multiple time-varying magnitude observations,  applied a method designed to extract time-translation invariant features from the time-series light curves of each object for future input into a classification system. These efforts re met with limited success due to noise and uneven sampling within the time-series data. Additionally, finely surveying these light curves is a processing intensive task. Fortunately, these algorithms are capable of multi-threaded implementations based on available resources. Therefore  propose a new system designed to utilize multiple intelligent agents that distribute the data analysis across multiple machines whilst simultaneously a porful intelligence service operates to constrain the light curves and eliminate false signals due to noise and local alias periods. This system will be highly scalable, capable of operating on a wide range of hardware whilst maintaining the production of ac-curate features based on the fitting of harmonic models to the light curves within the initial Structural Query Language database.
['Paul R. McWhirter', 'Sean Wright', 'Iain A. Steele', 'Dhiya Al-Jumeily', 'Abir Jaafar Hussain', 'Paul Fergus']
I am writing a research paper on a idea A Dynamic, Modular Intelligent-Agent Framework for Astronomical Light Curve Analysis and Classification
[{"from": "human", "value": "I am writing a research paper on a idea A Dynamic, Modular Intelligent-Agent Framework for Astronomical Light Curve Analysis and Classification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Modern time-domain astronomy is capable of collecting a staggeringly large amount of data on millions of objects in real time. This makes it almost impossible for objects to be identified manually. Therefore the production of methods and systems for the automated classification of time-domain astro-nomical objects is of great importance. The Liverpool Telescope has a number of wide-field image gathering instruments mounted upon its structure. These in-struments have been in operation since March 2009 gathering data of multi-degree sized areas of sky around the current field of view of the main telescope. Utilizing a Structured Query Language database established by a pre-processing operation upon the resultant images, which has identified millions of candidate variable stars with multiple time-varying magnitude observations,  applied a method designed to extract time-translation invariant features from the time-series light curves of each object for future input into a classification system. These efforts re met with limited success due to noise and uneven sampling within the time-series data. Additionally, finely surveying these light curves is a processing intensive task. Fortunately, these algorithms are capable of multi-threaded implementations based on available resources. Therefore  propose a new system designed to utilize multiple intelligent agents that distribute the data analysis across multiple machines whilst simultaneously a porful intelligence service operates to constrain the light curves and eliminate false signals due to noise and local alias periods. This system will be highly scalable, capable of operating on a wide range of hardware whilst maintaining the production of ac-curate features based on the fitting of harmonic models to the light curves within the initial Structural Query Language database."}]