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Development and application of a multi-criteria decision-support framework for planning rural energy supply interventions in low-income households in South Africa
Published 2022“…Problems in the public policy decision-making environments are typically complex and continuously evolve. …”
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Agentskapsteorie
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Little seeds : a prototype of collaborative-integrated, missional-diaconal praxis
Published 2023Get full text
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Reliable Outdoor Ai-Based Autonomous Uav Localization and Trajectory Tracking Using Cellular Networks
Published 2024“…We utilize conventional optimization methods to determine the optimal bound of the solution of the reliable UAV navigation problem. …”
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Queueing based resource allocation in cognitive radio networks
Published 2018Get full text
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A bi-criteria algorithm for the simultaneous minimization of makespan and number of tardy jobs on a single machine with sequence dependent set-up time
Published 2011ArticleFull Text AvailableAccess Repository -
Damping of electromechanical oscillations using power system stabilizers
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Reinforcement learning for power scheduling in a grid-tied pv-battery electric vehicles charging station
Published 2022“…Further, an advantage actor-critic (A2C) algorithm was developed and was used to solve the power scheduling problem. The two algorithms were tested using a 24-hour load, generation and utility grid tariff profiles under static optimization conditions. …”
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Efficient energy management in ultra-dense wireless networks
Published 2020“…The proposed solution to the formulated optimization problem makes use of constraint relaxation to transform the NP-hard problem into a more solvable, convex and linear optimization one. …”
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Traffic Engineering using Multipath Routing Approaches
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Multiobjective in-core fuel management optimisation for nuclear research reactors
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Reinforcement learning microservices scheduler in intelligent edge computing
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Decentralized algorithm of dynamic task allocation for a swarm of homogeneous robots
Published 2017“…The main contribution in this thesis is to maximize the overall efficiency of the system by minimizing the total time needed to accomplish the dynamic task allocation problem. The near-optimal allocation schemes are found using a novel hybrid decentralized algorithm for a dynamic task allocation in a swarm of homogeneous robots, where the number of the tasks is more than the robots present in the system. …”
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Machine learning methods for large deviations
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Inclusion of input saturation in the design of dynamically operable plants
Published 2014Get full text
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