Search Results - "Somu, Nivethitha"
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Evaluation of building energy demand forecast models using multi-attribute decision making approach
Published in Energy and built environment (01-06-2024)“…•GI-MARCOS, decision making model for building energy demand analysis is presented.•Gini index assigns objective weight to attributes in each phase of…”
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A computational model for ranking cloud service providers using hypergraph based techniques
Published in Future generation computer systems (01-03-2017)“…In a cloud marketplace, the existence of wide range of Cloud Service Providers (CSPs) makes it hard for the Cloud Users (CUs) to find an appropriate CSP based…”
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3
Occupancy estimation with environmental sensors: The possibilities and limitations
Published in Energy and built environment (01-02-2025)“…•Occupancy estimation modelled as classification and regression problem.•Environmental sensor data is useful for detecting presence/absence of occupants.•ML…”
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An efficient intrusion detection technique based on support vector machine and improved binary gravitational search algorithm
Published in The Artificial intelligence review (01-06-2020)“…‘Curse of Dimensionality’ and the trade-off between high detection rate and less false alarm rate make the design of an efficient and robust Intrusion…”
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5
A deep learning framework for building energy consumption forecast
Published in Renewable & sustainable energy reviews (01-03-2021)“…Increasing global building energy demand, with the related economic and environmental impact, upsurges the need for the design of reliable energy demand…”
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A hybrid model for building energy consumption forecasting using long short term memory networks
Published in Applied energy (01-03-2020)“…•eDemand, a data driven energy consumption forecasting model is developed.•The proposed model is designed for accurate short, mid, and long term…”
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A hybrid deep transfer learning strategy for thermal comfort prediction in buildings
Published in Building and environment (15-10-2021)“…Since the thermal condition of living spaces affects the occupants' productivity and their quality of life, it is important to design effective heating,…”
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IIVIFS-WASPAS: An integrated Multi-Criteria Decision-Making perspective for cloud service provider selection
Published in Future generation computer systems (01-02-2020)“…Cloud service provider selection, an important Multi-Criteria Decision Making (MCDM) problem involves intrinsic relations among the multiple alternatives,…”
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Multi-sensor data fusion framework for energy optimization in smart homes
Published in Renewable & sustainable energy reviews (01-04-2024)“…Advancements in Internet of Energy (IoE) technologies drive the development of several energy efficient frameworks for better energy optimization, economic…”
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10
An efficient intrusion detection system based on hypergraph - Genetic algorithm for parameter optimization and feature selection in support vector machine
Published in Knowledge-based systems (15-10-2017)“…Realization of the importance for advanced tool and techniques to secure the network infrastructure from the security risks has led to the development of many…”
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A Hypergraph and Arithmetic Residue-based Probabilistic Neural Network for classification in Intrusion Detection Systems
Published in Neural networks (01-08-2017)“…Over the past few decades, the design of an intelligent Intrusion Detection System (IDS) remains an open challenge to the research community. Continuous…”
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A trust centric optimal service ranking approach for cloud service selection
Published in Future generation computer systems (01-09-2018)“…Cloud service selection, a promising research directive provides an intelligent solution via. service ranking based on the Quality of Service (QoS) attributes…”
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13
A multilayer perceptron model for anomaly detection in water treatment plants
Published in International journal of critical infrastructure protection (01-12-2020)“…•A multi-layer perceptron model is proposed for anomaly detection in industrial control systems.•The hyperparameters of the MLP were fine-tuned to achieve…”
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14
An improved robust heteroscedastic probabilistic neural network based trust prediction approach for cloud service selection
Published in Neural networks (01-12-2018)“…Trustworthiness is a comprehensive quality metric which is used to assess the quality of the services in service-oriented environments. However, trust…”
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A rough set-based hypergraph trust measure parameter selection technique for cloud service selection
Published in The Journal of supercomputing (01-10-2017)“…Selection of trustworthy cloud services has been a major research challenge in cloud computing, due to the proliferation of numerous cloud service providers…”
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IBGSS: An Improved Binary Gravitational Search Algorithm based search strategy for QoS and ranking prediction in cloud environments
Published in Applied soft computing (01-03-2020)“…Quality of Service (QoS) value prediction and QoS ranking prediction have their significance in optimal service selection and service composition problems. QoS…”
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A hybrid approach using rough set theory and hypergraph for feature selection on high-dimensional medical datasets
Published in Soft computing (Berlin, Germany) (01-12-2019)“…‘Curse of Dimensionality’—massive generation of high-dimensional medical datasets from various biomedical applications hardens the data analytic process for…”
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18
An improved rough set approach for optimal trust measure parameter selection in cloud environments
Published in Soft computing (Berlin, Germany) (01-11-2019)“…The existence of a multitude of cloud service providers (CSPs) for each service type increases the difficulty in the identification of appropriate and…”
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19
Hypergraph Based Feature Selection Technique for Medical Diagnosis
Published in Journal of medical systems (01-11-2016)“…The impact of internet and information systems across various domains have resulted in substantial generation of multidimensional datasets. The use of data…”
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EnsembleNTLDetect: An Intelligent Framework for Electricity Theft Detection in Smart Grid
Published 09-10-2021“…Artificial intelligence-based techniques applied to the electricity consumption data generated from the smart grid prove to be an effective solution in…”
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