Exploratory data analysis and empirical modelling of stationary processes by use of genetic programming by Chemaly, Timothy Paul

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On the theory and practice of anomaly detection in time series by Barrish, Daniel

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Scheduling coal handling processes using metaheuristics

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An explicit finite difference method for analyzing hazardous rock mass by Basson, Gysbert

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Mobile robot optimum trajectory Development using a hybrid reactive navigation model

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A method of voltage tracking for power system applications

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A learning framework for zero-knowledge game playing agents

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Calibrating a stochastic SIR-model to simulated data using different calibration methods : a tutorial & comparison of methods by Van Staden, Wynand-Junior

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A decision support system for telemedicine needs assessments in South Africa by Treurnicht, Maria Jacoba

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Fast and Accurate Automatic Design of Spiral Inductors from High-Level Specification by Ismail, Heba

“…A further approach that has been extensively emerging recently is undergoing optimization algorithms, such as sequential quadratic programming, simulated annealing, artificial neural network, genetic algorithms… etc. …”
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Reinforcement learning for routing in communication networks by Andrag, Walter H.

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Competitive co-evolution of trend reversal indicators using particle swarm optimisation

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Order sequencing and SKU arrangement on a unidirectional picking line by Matthews, Jason

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Sparse coding for speech recognition

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Solving dynamic multi-objective optimisation problems using vector evaluated particle swarm optimisation

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Use of a feeding and activity behaviour monitor in Jersey dairy cows during the transition period by Du Toit, Derek Auret

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The artificial immune system with evolved lymphocytes

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Calibrating models to data: a comparison of methods by Suboi, Zenabu

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Navigating the Future Advancing Autonomous Vehicles through Robust Target Recognition and Real-Time Avoidance by Hussein, Mohammed Ahmed Mohammed

“…We are using as our base a particular object recognition algorithm (YOLOv7) and a particular simulation environment (CARLA). …”
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Particle swarm optimisation in dynamically changing environments - an empirical study

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