A systematic review of hidden Markov models and their applications
B Mor, S Garhwal, A Kumar - Archives of computational methods in …, 2021 - Springer
The hidden Markov models are statistical models used in many real-world applications and
communities. The use of hidden Markov models has become predominant in the last …
communities. The use of hidden Markov models has become predominant in the last …
Review of low voltage load forecasting: Methods, applications, and recommendations
The increased digitalisation and monitoring of the energy system opens up numerous
opportunities to decarbonise the energy system. Applications on low voltage, local networks …
opportunities to decarbonise the energy system. Applications on low voltage, local networks …
DB-Net: A novel dilated CNN based multi-step forecasting model for power consumption in integrated local energy systems
In the era of cutting edge technology, excessive demand for electricity is rising day by day,
due to the exponential growth of population, electricity reliant vehicles, and home …
due to the exponential growth of population, electricity reliant vehicles, and home …
Short-term prediction of residential power energy consumption via CNN and multi-layer bi-directional LSTM networks
Excessive Power Consumption (PC) and demand for power is increasing on a daily basis,
due to advancements in technology, the rise in electricity-dependent machinery, and the …
due to advancements in technology, the rise in electricity-dependent machinery, and the …
A survey on machine learning in Internet of Things: Algorithms, strategies, and applications
In the IoT and WSN era, large number of connected objects and sensing devices are
dedicated to collect, transfer, and generate a huge amount of data for a wide variety of fields …
dedicated to collect, transfer, and generate a huge amount of data for a wide variety of fields …
Towards developing a systematic knowledge trend for building energy consumption prediction
The rapid depletion of natural sources of energy, coupled with increasing global population
has triggered the emergence of various techniques and strategies for building energy …
has triggered the emergence of various techniques and strategies for building energy …
Impact of internet of things paradigm towards energy consumption prediction: A systematic literature review
YL Cheng, MH Lim, KH Hui - Sustainable Cities and Society, 2022 - Elsevier
The contribution of buildings to energy consumption (both residential and commercial) is
expected to gradually increase by 2040 in developed countries globally. Energy demand is …
expected to gradually increase by 2040 in developed countries globally. Energy demand is …
[HTML][HTML] Energy management of smart homes over fog-based IoT architecture
Existing research studies on home automation systems mostly conserve energy by modeling
the occupancy of users within home. Some others apply statistical approaches on the survey …
the occupancy of users within home. Some others apply statistical approaches on the survey …
An ensemble energy consumption forecasting model based on spatial-temporal clustering analysis in residential buildings
Due to the availability of smart metering infrastructure, high-resolution electric consumption
data is readily available to study the dynamics of residential electric consumption at finely …
data is readily available to study the dynamics of residential electric consumption at finely …
A prediction methodology of energy consumption based on deep extreme learning machine and comparative analysis in residential buildings
In this paper, we have proposed a methodology for energy consumption prediction in
residential buildings. The proposed method consists of four different layers, namely data …
residential buildings. The proposed method consists of four different layers, namely data …