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1
A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…The clique partitioning problem has important applications in many areas including VLSI design automation, scheduling, and resources allocation. In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
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2
A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs†
Published 2010“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …”
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3
Deep Reinforcement Learning for Resource Constrained HLS Scheduling
Published 2022“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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4
A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS
Published 2020Get full text
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5
Prediction of EV Charging Behavior Using Machine Learning
Published 2021“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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6
A Framework for Predictive Modeling in Sustainable Projects
Published 2012Get full text
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7
Machine Learning-Based Approach for EV Charging Behavior
Published 2021Get full text
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8
Microwave brain imaging system to detect brain tumor using metamaterial loaded stacked antenna array
Published 2022“…The antenna is comprised of metamaterial-loaded with three substrate layers, including two air gaps. One 1 × 4 MTM array element is used in the top layer and middle layer, and one 3 × 2 MTM array element is used in the bottom layer. …”
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9
Approximate XML structure validation technical report
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10
Identification And Weather Sensitivity Of Physically Based Model Of Residential Air-Conditioners For Direct Load Control: A Case Study
Published 2020“…An online maximum likelihood based-identification algorithm is developed. The required hardware and system instrumentation are detailed. …”
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