Sökning: "Random search"

Visar resultat 1 - 5 av 141 uppsatser innehållade orden Random search.

  1. 1. Spatio-temporal analysis of COVID-19 in Västra Götaland, Sweden

    Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Natalia Andreeva; [2023-08-23]
    Nyckelord :;

    Sammanfattning : Spatio-temporal analysis of COVID-19 data with the two different statistical approaches is the main objective of this thesis. The first classical approach, the Endemic-Epidemic framework (Held et al., 2005) is a class of multivariate time-series models for the incidence counts, obtained from the surveillance systems. LÄS MER

  3. 2. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Jiayi Feng; [2023]
    Nyckelord :DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Embedded Systems; DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Inbyggda system;

    Sammanfattning : Customized Deep Neural Network (DNN) accelerators have been increasingly popular in various applications, from autonomous driving and natural language processing to healthcare and finance, etc. However, deploying them directly on embedded system peripherals within real-time operating systems (RTOS) is not easy due to the paradox of the complexity of DNNs and the simplicity of embedded system devices. LÄS MER

  4. 3. Exploring New Physics Through Collider and Gravitational Wave Measurements with Artificial Neural Networks: the Case Study of QCD-like Technicolor

    Magister-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Teoretisk partikelfysik - Geonomgår omorganisation

    Författare :Ashar Ahmed Kamal; [2023]
    Nyckelord :Artificial Neural Networks; ANN; Beyond the Standard Model; BSM; parameter space scan; Physics and Astronomy;

    Sammanfattning : With physicists actively exploring Beyond the Standard Model (BSM) theories that may fill in the gaps of the Standard Model (SM), a fundamental question arises: which parameters hold physical significance? In this thesis, we present our initial progress towards the development of a model-independent artificial intelligence framework designed for conducting parameter space scans in BSM scenarios. Our framework incorporates several publicly available high-energy physics packages, namely SPheno, HiggsBounds, HiggsSignals, and CosmoTransitions. LÄS MER

  5. 4. Implementing and comparing challengers to popular multi-objective algorithms for unit test cases generation

    Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för programvaruteknik

    Författare :Elias Lindfors; [2023]
    Nyckelord :multi-objective; evosuite; genetic; algorithm;

    Sammanfattning : The topic of multi-objective algorithms has been researched for many years, where hundreds of multi-objective algorithms have been developed. With the field of search-based software engineering attracting use-cases, more research on which algorithms are fitting the area is still lacking. LÄS MER

  7. 5. Supervised Failure Diagnosis of Clustered Logs from Microservice Tests

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Amanda Strömdahl; [2023]
    Nyckelord :Supervised Learning; Failure Diagnosis; Clustered Log Data; Random Forest; SVM; MLP; Övervakad inlärning; feldiagnos; klustrad logg-data; Random Forest; SVM; MLP;

    Sammanfattning : Pinpointing the source of a software failure based on log files can be a time consuming process. Automated log analysis tools are meant to streamline such processes, and can be used for tasks like failure diagnosis. This thesis evaluates three supervised models for failure diagnosis of clustered log data. LÄS MER