Optimal cruise control of heavy-haul trains equipped with electronic controlled pneumatic brake systems

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Integrated Circuits Parasitic Capacitance Extraction Using Machine Learning and its Application to Layout Optimization by Saleh, Mohamed Saleh Abouelyazid

“…On the other hand, the new parasitic extraction accuracy requirements also added more challenges on existing parasitic-aware routing optimization methods, where simplified parasitic models are used to optimize layouts. …”
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Energy savings and maintenance optimization of energy-efficient lighting retrofit projects incorporating lumen degradation

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Selection and metabolic characterization of mesophylic starter cultures for optimizing the sensory attributes of fruit flavoured Maas by Arendse, Garron Mark

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A study of gradient based particle swarm optimisers

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The effect of covid-19 lockdown on healthcare utilisation and hospital mortality in children < 5 years of age in a large Cape Town District, South Africa by Elmi, Noradin

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Optimized discharge excitation techniques for short pulse gas lasers : TEA CO2 laser by Kyeyune, Farooq

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Short-term wind power forecasting using artificial neural networks-based ensemble model by Chen,Qin

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A feasibility study of trajectory optimisation on a low-cost legged platform with open loop control. by Coetzer, Margarethe

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Optimal energy-efficiency retrofit and maintenance planning for existing buildings considering green building policy compliance

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End-to-end security mechanisms for the optimized link state routing protocol for wireless ad hoc networks by Asherson, Stephen Warren

“…This performance degradation exists primarily due to the key management problems of the HORS one-time signature scheme, particularly regarding the process of public key distribution in a wireless network environment which lacks reliable broadcast transmissions and is subject to packet loss. …”
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Characterization of the high temperature caustic conditioning process for optimized gold recovery from double refractory ores

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Using particle swarm optimisation to train feedforward neural networks in dynamic environments

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Ghana prayer camp liturgies for spiritual support regarding mental suffering : a practical theological approach

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Crafting asset allocation for a re-insurer via portfolio optimisation by Abdulla, Mubeen

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3D turning analysis of a Bipedal Robot by Pretorius, Dean

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Optimal energy management for a grid-tied solar PV-battery microgrid: A reinforcement learning approach by Muriithi, Grace

“…Secondly, a deep Q network (DQN) method that uses recent learning algorithm enhancements, including experience replay and target network, is developed to learn the system uncertainties, including load demand, grid prices and volatile power supply from the renewables solve the optimal energy management problem. Unlike the Q-learning method, which updates the Q-function using a lookup table (which limits its scalability and overall performance in stochastic optimization), the DQN method uses a deep neural network that approximates the Q- function via statistical regression. …”
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Optimal integration of solar home systems and appliance scheduling for residential homes under severe national load shedding

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Optimizing the adaptation rate of feedlot steers dosed with Megasphaera elsdenii NCIMB 41125 and fed high starch diets

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