Essays about: "Extreme learning machine"
Showing result 1 - 5 of 66 essays containing the words Extreme learning machine.
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1. Drivers of sea level variability using neural networks
University essay from Göteborgs universitet/Institutionen för geovetenskaperAbstract : Understanding the forcing of regional sea level variability is crucial as many people all over the world live along the coasts and are endangered by extreme sea levels and the global sea level rise. The adding of fresh water into the oceans due to melting of the Earth’s land ice together with thermosteric changes has led to a rise of the global mean sea level with an accelerating rate during the twentieth century. READ MORE
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2. Monthly heatwave prediction in Sweden based on Machine Learning techniques with remote sensing data
University essay from KTH/Hållbar utveckling, miljövetenskap och teknikAbstract : Heatwave events as a kind of extreme climate event, have plagued the human race for the past few years. It severely influences people’s life quality, sometimes even leads to some serious diseases. In order to alleviate the possible damages heatwave events can do, some targeted actions are necessary and forecasting heatwaves is one of them. READ MORE
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3. Control Aid Implementation -Modelling and simulation of triple extruder-
University essay from Lunds universitet/Kemiteknik (CI)Abstract : In the production of their High Voltage Direct Current Cables (HVDC) and High Voltage Alternating Current Cables (HVAC), NKT uses triple extruders to create layers of insulation and semi-conduction. A model to predict the effect of extruder inputs on the cable’s insulation and semi-conducting layers has been created and trained to predict the extruder in discrete time. READ MORE
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4. COMPARATIVE ANALYSIS OF MACHINE LEARNING LOAD FORECASTING TECHNIQUES
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Load forecasting plays a critical role in energy management, and power systems, enabling efficient resource allocation, improved grid stability, and effective energy planning and distribution. Without accurate very short term load forecasting, utility management companies face uncertain load patterns, unrealistic prices, and poor infrastructure planning. READ MORE
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5. Multi-Class Classification for Predicting Customer Satisfaction : Application of machine learning methods to predict customer satisfaction at IKEA
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : Gaining a comprehensive understanding of the features that contribute to customer satisfaction after contact with IKEA’s Remote Customer Meeting Points (RCMPs) is essential for implementing effective remedial measures in the future. The aim of this project is to investigate if it is possible to find key features that influence customer satisfaction and to use these to predict customer satisfaction. READ MORE