Essays about: "MLP"

Showing result 1 - 5 of 45 essays containing the word MLP.

  1. 1. Pulse Repetition Interval Modulation Classification using Machine Learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Eric Norgren; [2019]
    Keywords : machine learning; radar; radar pulses; radar signals; pulseradar; pulse repetition interval; modulation; classification; LSTM; long short term memory; feature extraction; saab; ai; artifical intelligence; radar warning receiver; rwr; neural network; maskininlärning; radar; radarpulser; radar signaler; pulsradar; pulsrepetitionsintervall; modulationstyp; modulering; klassificering; LSTM; long short term memory; särdrag; saab; ai; artificiell intelligens; radarvarnare; rwr; neuralt nätverk;

    Abstract : Radar signals are used for estimating location, speed and direction of an object. Some radars emit pulses, while others emit a continuous wave. Both types of radars emit signals according to some pattern; a pulse radar, for example, emits pulses with a specific time interval between pulses. READ MORE

  2. 2. A shady future for Brazilian agriculture? Obstacles to and opportunities for agroforestry as a sustainable alternative to current agricultural practices

    University essay from Lunds universitet/LUCSUS

    Author : Asger Mindegaard; [2019]
    Keywords : agriculture; agroforestry; sustainability transitions; multi-level perspective; Brazil; sustainability science; Social Sciences;

    Abstract : As the negative environmental impacts of contemporary agriculture become still more evident and widespread, the question of how to feed future generations while preserving the vital stability of the planet’s environment is more urgent than ever. Major institutions are targeting the environmental sustainability of agriculture, internationally as well as in Brazil. READ MORE

  3. 3. Deep Learning models for turbulent shear flow

    University essay from KTH/Numerisk analys, NA

    Author : Prem Anand Alathur Srinivasan; [2018]
    Keywords : ;

    Abstract : Deep neural networks trained with spatio-temporal evolution of a dynamical system may be regarded as an empirical alternative to conventional models using differential equations. In this thesis, such deep learning models are constructed for the problem of turbulent shear flow. READ MORE

  4. 4. Hyperloop in Sweden : Evaluating Hyperloops Viability in the Swedish Context

    University essay from KTH/Industriell ekonomi och organisation (Inst.); KTH/Industriell ekonomi och organisation (Inst.)

    Author : Fredrik Magnusson; Fredrik Widegren; [2018]
    Keywords : Hyperloop; Hyperloop in Sweden; Transportation; Infrastructure; Transport Market Dynamics; The Swedish Transport Market; New Mode of Transportation; Emerging Technologies; Disruptive Innovation; Diffusion of Innovation; Characteristics of Diffusion; Technical Transition; Socio-technical Transition; Transformational Pressure; Window of Opportunity; Multi-Level Perspective MLP ; Technology Readiness Level TRL ; Hyperloop; Hyperloop i Sverige; Transport; Infrastruktur; Transportmarknadens Dynamik; Den Svenska Transportmarknaden; Nya Transportsätt; Framväxande Teknik; Disruptiv Innovation; Diffusion av Innovation; Egenskaper för Spridning av Innovation; Teknisk övergångsteori; Socio-teknisk övergångsteori; Transformationstryck; Möjlighetsfönster; Perspektiv i Multipla Nivåer MLP ; Teknisk Mogenhetsnivå TRL ;

    Abstract : Transportations role in society is increasingly important and today it has a prominent role in business, citizens lives as well as in the world economy. The increasing globalization and urbanization puts significant pressure on the existing transport system, with increasing demand for high-speed travel. READ MORE

  5. 5. Model comparison of patient volume prediction in digital health care

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Sasha Hellstenius; [2018]
    Keywords : Recurrent Neural Networks; LSTM; Patient Volume Prediction; Digital Healthcare;

    Abstract : Accurate predictions of patient volume are an essential tool to improve resource allocation and doctor utilization in the traditional, as well as the digital health care domain. Varying methods for patient volume prediction within the traditional health care domain has been studied in contemporary research, while the concept remains underexplored within the digital health care domain. READ MORE