Digital Cities Roadmap. Группа авторов

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learning method is facilitated across a number of ML frameworks and resources. The challenge of choosing the best platform in order to data analytics flow sharing can also be achieved from alternative viewpoints challenging despite the growing amount of such toolkits. There is generally no one toolkit that completely suits all challenges (Table 1.6) and includes remedies. Some of the toolkits available could overlap, with benefits and drawbacks.

      Table 1.6 Difference between deep learning and machine learning tools [56].

Tool Creator OS Open source? Written In Interface CUDA support? Algorithms Release date
Tensor Flow Google Brain team Linux. Mac OS X (Windows support on road map Yes C++, Python Python, C/ C++ Yes Deep learning algorithm: RNN, CN, RBM and DUN. Novembeir 2015
Theano Universit de Montral Cross-platform Yes Python Python Yes Deep learning algorithm: RNN, CN, RBM and DBN. September 2007
H20 H20.ai Linux, Mac OS, Microsoft Windows And Cross-platform inch Apache HDFS; Amazon EC2, Google Compute Engine, and Microsoft Azure. Yes Java, Scala, Python, R Python, R No Algorithms for classification, clustering, generalized linear models, statistical analysis, ensembles, optimization tools, data pre-processing options and deep neural networks. August 2011
Deeplearning4j Various. Original author Adam Gibson Linux, OSX, Windows, Android, CyanogenMod (Cross-platform) Yes Java, Scala, C, CUDA Java, Scala, CIo-jure Yes Deep learning algorithms including: RBM, DBN. RNN. deep autoencoder August 2013
MLlib Spark Apache Software Foundation. UC Berkeley AMPLab, Databricks Microsoft Windows, OS X, Linux Yes Scala. Java, Python, R Scala, Java, Python. R No Classification, regression, clustering, dimensionality reduction, and collaborative filtering May 2014
Azure Dave Cutler from Microsoft Microsoft Windows, Linux No C++ C++, Java. ASP.NET, PHP. Nodejs, Python Yes Classification, regression, clustering October 2010
Torch Ronan Collobert, Koray Kavukcuoglu, Clement Farabet Linux. Android, Mac OS XTiOS Yes C, Lua Lua, LuaJlT. C, utility library for C++/ OpenCL Yes Deep algorithms October 2002
MOA University of Waikato Cross-platform Yes Java GUI, the commandline. and Java No ML algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) November 2014
Caffe Berkeley Vision and Learning Center. community contributors Ubuntu, OS X, AWS, unofficial Android port, Windows support by Microsoft Research, unofficial Windows port Yes C++, Python C++, command line. Python, MATLAB Yes Deep learning algorithms: CN, and RNN December 2012

       1.10.7 Big Data Research Applications for SBs in Real-Time

       1.10.8 Implementation of the ML Concept in the SB Context

      Figure 1.25 illustrates specific measures to forecast an event in the SB sense by utilizing ML methods.

      On the other hand, the aim of optimization is to optimize long-lasting gains by proper decisions. Strengthening learning with these issues can be used. Many optimization issues may be treated as predicting issues such that benefit is estimated for different activities and the activity with the largest income is chosen. The most important form in optimization is decision-making. A variety of factors and compromises about the effects of specific environmental locations need to be addressed.

       Smart Building Services Taxonomy

      The taxonomy of SB resources essential domains is shown in Figure 1.26. Lighting service connects the well-being of occupants in SBs that have sensors that save energy when lights are not needed, based on their operation. Power and electricity can supply a percentage of SB power consumption with renewable energy sources. HVAC implies the heating, ventilation and air conditioning device, built for the comfort of citizens and an efficient ambient contact. The water resources program aims at growing conservation and maximizing resource recovery for water supply.

      Smart building service taxonomy is related to the maintenance of electronic doors, biometrics and SB security cameras devices. The Control Center offers management and decision-making for apps. The automated apps


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