Bigdata Analytics and Engineering Lab

Regardless of kinds of industry, demand and risk predictions of operation are significant issues to the operators. Because predictions can make the operators to prepare and handle the market and the problems in advance. In addition, it has become possible to predict accurately by using data for prediction. Thus, it is growing that the interest and importance of predictive analytics based on data. In our laboratory, we are contributing to advance of predictive analytics by studying these topics; 1. Development of predictive models using field data and related other data and 2. Establishment of services and platforms for effective operation by prediction methodologies and result.

• Studying prediction methodology based on machine learning for facility predictive maintenance by state monitoring and prediction using facility data
• Drawing the optimal resources level from the simulation based on the prediction result of analytic and predictive algorithm that developed in the past; and, prediction of various situation that can occur in the field by inferring the operating prediction distribution and making the predictive process model from data.
• Study the predictive methodology according to the wider inference of field situations under the conditions that was done before.
• Development of multi-layered LSTM predictive analytics methodology for exact medium and long-term prediction of resource pattern and demand by using data.

• Development and construction the services of facility state prediction based on monitoring and facility data pattern analytics; the services use the data that was collected in real time from IoT sensors.
• Optimization of operating plans using reinforcement learning based on using operating the facility data comprehensively including the predictive results of the uncertain outdoor operating facility states.
• Developing the data analytic and predictive platform that can be used by domain expert easily with introduction of the methodologies like process mining, statistical methods, simulation, and artificial intelligence for operating big data analytics.