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Modeling and optimization of biogas production from a waste digester using artificial neural network and genetic algorithm
(
Elsevier B.V.
, 2009 , Article)
Artificial neural networks (ANNs) and genetic algorithms (GA) are considered among the latest tools that are used to solve complicated problems that cannot be solved by conventional solutions. The present study utilizes ...
Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach
(
Elsevier Ltd
, 2014 , Article)
Recently, the increasing energy demand has caused dramatic consumption of fossil fuels and unavoidable raising energy prices. Moreover, environmental effect of fossil fuel led to the need of using renewable energy (RE) to ...
Distributed spectrum sensing of correlated observations in cognitive radio networks
(2013 , Conference Paper)
In this paper, Collaborative Spectrum Sensing (CSS) as one of the most efficient sensing approaches in Cognitive Radio Networks (CRNs) is investigated when the Secondary Users (SUs) observations are assumed to be correlated. ...
Lifetime maximization for greedy selective relay strategies
(2009 , Conference Paper)
In this paper we propose a new algorithm for selective relay strategies with Amplify-and-Forward (AF) relays which improves the relay network lifetime. The lifetime of the relay network is defined as the maximum number of ...
Underlay cognitive radio: What is the impact of carrier aggregation and relaying on throughput?
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
In this paper, we investigate joint relay selection and optimal power allocation, as a means to maximize the achievable rate of an underlay cooperative cognitive radio with carrier aggregation, taking into account the ...
The effect of additional statistical side information on multiple antenna spectrum sensing
(2012 , Conference Paper)
In this paper, we consider the problem of multiple antenna spectrum sensing in Cognitive Radios (CR) when some or all parameters are unknown. The Generalized Likelihood Ratio (GLR) test is the convectional method to solve ...
New Deep Learning-Based Approach for Wind Turbine Output Power Modeling and Forecasting
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
An intelligent machine learning-based method is developed in this paper for modeling and prediction of the wind turbine (WT) output power. The developed technique makes use of the advanced machine learning models for ...
Optimization models in emergency logistics: A literature review
(
Elsevier
, 2012 , Article Review)
Optimization modeling has become a powerful tool to tackle emergency logistics problems since its first adoption in maritime disaster situations in the 1970s. Using techniques of content analysis, this paper reviews ...
Metaheurestic algorithm based hybrid model for identification of building sale prices
(
Springer Science and Business Media Deutschland GmbH
, 2021 , Book chapter)
The overall cost of a building depends on several variables such as economical, project physical and financial variables. The CCB (construction cost of building) also depends on deviations of several indices which are not ...
DRL-HEMS: Deep Reinforcement Learning Agent for Demand Response in Home Energy Management Systems Considering Customers and Operators Perspectives
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
With the smart grid and smart homes development, different data are made available, providing a source for training algorithms, such as deep reinforcement learning (DRL), in smart grid applications. These algorithms allowed ...