Abstract
Long Short Term Memory Network is the variant of RNN (Recurrent Neural Network) popularly used in various domains, particularly for sequence prediction tasks. For deep networks, number of hidden layers in the network is high and thus, the time complexity of the network increases. Moreover, with the increase in the size of datasets, it becomes very difficult to tune these complex networks manually (as the network may take several days/weeks to run). Thus, to minimize the time required to run an algorithm and for better accuracy, there is a need to automate the task of tuning the parameters of the network. To automatically tune the parameters of the networks, various researchers have used numerous Metaheuristic approaches like Ant Colony Optimization, Genetic Algorithm, Simulated Annealing etc. in the past which provides us with the near optimal solution. In the proposed ABC_LSTM algorithm, traditional Artificial Bee Colony algorithm has been implemented to optimize the number of hidden neurons of LSTM networks with 2 hidden layers. Based on the experimental results, it can be concluded that up to a certain point increasing the number of bees and iterations gives us the solution with the least MAE value, thereby improving the accuracy of the model.
Highlights
Big data is a term defined for huge amount of data generated at a very high speed containing values of different data types revealing some important information
We have reviewed various machine learning and data mining techniques used for analysis of Big Data and it was interpreted that Deep Learning, Online Learning and Incremental Learning are popular techniques used in the field of big data[2], [3]
We have proposed hybrid ABC_LSTM algorithm in which LSTM RNN neural network is used for prediction of temperature for 1 hour time lag while ABC algorithm is used to automate the choice of number of hidden layers for the LSTM network
Summary
Big data is a term defined for huge amount of data generated at a very high speed containing values of different data types revealing some important information. Which can effectively store and process big datasets Among these above mentioned tools, Spark is a very popular open source tool developed by Apache for big datasets, which has an advantage of in-memory data processing and support for iterative tasks. Pandas is another open source library which provides dataframes that supports in-memory computing and is limited to the size of server. Genetic Algorithm are the various Metaheuristic techniques which are gaining immense popularity these days Among these techniques, Artificial Bee Colony has been widely used in numerous domains as it has the capability of finding global optimum solution. Scout bees are the bees which are not selected after some predefined number of trials and are abandoned from the search process
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