In the future, as populations grow and more end-user applications become available, current traditional electrical distribution substation will not be able to fully accommodate new that may arise. Consequently, there numerous difficulties, including network congestion, latency, jitter, and, in worst-case scenario, failure, among other things. Thus, purpose of this study is assist decision maker...

Cloud computing has rapidly emerged as a model for delivering Internet-based utility services. Infrastructure Service (IaaS) is one of the most important and growing models in cloud computing. Scalability, quality service, optimum utility, decreased overheads, higher throughput, reduced latency, specialised environment, cost-effectiveness, streamlined interface are some essential elements IaaS....

Machine Learning (ML) algorithms have opened up new possibilities for the acquisition and processing of documents in Information Retrieval (IR) systems. Indeed, it is now possible to automate several labor-intensive tasks related to documents such as categorization and entity extraction. Consequently, the application of machine learning techniques for various large-scale IR tasks has gathered s...

The scalability of machine learning (ML) algorithms has become increasingly important due to the ever increasing size of datasets and increasing complexity of the models induced. Standard approaches for dealing with this issue generally involve developing parallel and distributed versions of the ML algorithms and/or reducing the dataset sizes via sampling techniques. In this paper we describe a...

ML 2.0: In this paper, we propose a paradigm shift from the current practice of creating machine learning models that requires months-long discovery, exploration and “feasibility report” generation, followed by re-engineering for deployment, in favor of a rapid 8 week long process of development, understanding, validation and deployment that can executed by developers or subject matter experts ...

Nowadays machine learning (ML), including Artificial Neural Networks (ANN) of different architectures and Support Vector Machines (SVM), provides extremely important tools for intelligent geoand environmental data analysis, processing and visualisation. Machine learning is an important complement to the traditional techniques like geostatistics. This paper presents a review of several contempor...

evaporation is a fundamental parameter in the hydrological cycle. this study examines the performance of m5model tree and artificial neural network (ann) models in estimating potential evapotranspiration calculated bypenman- monteith and hargreaves- samani equations. daily weather data from two meteorological stations in asemi-arid climate of iran, namely kerman and zahedan, were collected duri...

In this position paper, we describe our vision of the future of machinebased programming through a categorical examination of three pillars of research. Those pillars are: (i) intention, (ii) invention, and (iii) adaptation. Intention emphasizes advancements in the human-to-computer and computer-to-machine-learning interfaces. Invention emphasizes the creation or refinement of algorithms or cor...