Classi cation of magnetic configurations using machine learning algorithms

Classi cation of magnetic configurations using machine learning algorithms

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.

Bibliografiske detaljer
Main Authors:	Bokul, Saffat, Abdus Shukur, Samiha Sabrin Md, Ahmed, Saquib
Andre forfattere:	Alam, Md. Ashraful
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2019
Fag:	Convolutional Neural Network Support vector machine Principle component analysis Skyrmion Ferromagnetic Spin-spira Antiskyrmion Anti-ferromagnetic Topological Machine learning Computer algorithms Machine learning > Mathematical models
Online adgang:	http://hdl.handle.net/10361/12825

Lignende værker

Performance evolution of Spin Valve transistor
af: Rashid, Shahriar, et al.
Udgivet: (2019)

Performance evolution of spin valve transistor
af: Rashid, Shahriar, et al.
Udgivet: (2018)

Influence of 𝑳𝒊+ Substitution on Magnetic and Electrical Properties of 𝑳𝒊𝒙𝑪𝒖𝟎.𝟓𝒁𝒏𝟎.𝟓−𝟐𝒙𝑭𝒆𝟐+𝒙𝑶𝟒
af: Mustafa, Anjum
Udgivet: (2020)

Chronic kidney disease detection using ensemble classi ers and feature set reduction
af: Shawan, Naveed Rahman, et al.
Udgivet: (2019)

Performance analysis of machine learning classi ers for detecting PE malware
af: Azmee, ABM.Adnan, et al.
Udgivet: (2020)

Heart disease prediction using machine learning algorithms
af: Ali, Musfiq, et al.
Udgivet: (2019)

Public vehicle ETA system using machine learning
af: Kabir, Md. Miraz, et al.
Udgivet: (2018)

Predicting depression in Bangladeshi undergraduates using machine learning
af: Choudhury, Ahnaf Atef, et al.
Udgivet: (2019)

Analysis of the impact of online education using EEG signals and machine learning algorithms
af: Hoque, Ehsanul, et al.
Udgivet: (2021)

Alumni opportunities using machine learning
af: Siaum, Arshif Sharlimin, et al.
Udgivet: (2019)

Machine learning as an indicator for breast cancer prediction
af: Shadman, Tahsin Mohammed, et al.
Udgivet: (2019)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
af: Toufique, S.M, et al.
Udgivet: (2024)

Pattern recognition with Quantum Support Vector Machine(QSVM) on near term quantum processors.
af: Ahmed, Sajjad
Udgivet: (2019)

Observing mega cities to grow from space and predicting its growth using machine learning techniques
af: Chakma, Mitesh, et al.
Udgivet: (2018)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
af: Alhossen, Md., et al.
Udgivet: (2021)

A machine learning approach to detect depression and anxiety using supervised learning
af: Ullas, Md Tahmidur Rahman, et al.
Udgivet: (2019)

Demystifying second hand car market in Bangladesh using multimodal machine learning techniques
af: Islam, Roman, et al.
Udgivet: (2024)

Detection of acute Lymphocytic Leukemia (ALL) and its type by image processing and machine learning
af: Chowdhury, Himadri, et al.
Udgivet: (2019)

Predicting climate induced floods using machine learning
af: Saleh, Chowdhury Nafis, et al.
Udgivet: (2022)

Crop prediction based on geographical and climatic data using machine learning and deep learning
af: Alif, Al Amin, et al.
Udgivet: (2019)

Application of machine learning in credit risk assessment: a prelude to smart banking
af: Dhruba, Mir Ishrak Maheer, et al.
Udgivet: (2019)

The influence of neuromarketing: machine learning based empirical analysis
af: Muktadir, MD. Abdullah Al, et al.
Udgivet: (2024)

Deep learning approaches for Bengali cyberbullying cetection on social media: a comparative study of BiLSTM, BiGRU and BERT models
af: Fahim, Kaji Mehedi Hasan, et al.
Udgivet: (2024)

A Study of gainful employment of learners receiving skills training in the informal sector using Machine Learning
af: Raizan, Syed Ahsan, et al.
Udgivet: (2021)

Financial factors analysis for acquisition premium and anticipation using extreme gradient boosting and deep recurrent neural network
af: Rayhan, Mohammad, et al.
Udgivet: (2020)

Fault detection in waste water treatment plant using statistical analysis & machine learning
af: Haque, Md. Ezazul, et al.
Udgivet: (2019)

Genetic algorithms in search, optimization, and machine learning /
af: Goldberg, David E. (David Edward), 1953-
Udgivet: (1989)

Machine Learning /
af: Mitchell, Tom M. (Tom Michael), 1951-
Udgivet: (1997)

Pattern recognition and machine learning /
af: Bishop, Christopher M.
Udgivet: (2006)

An implementation and analysis of deep learning models for the detection of wheat diseases
af: Zubair, Ahmad, et al.
Udgivet: (2024)

Real-time foul detection in football matches using machine learning techniques
af: Siddiqui, Bishal Sadi, et al.
Udgivet: (2024)

Health monitoring IoT device with risk prediction using cloud computing and machine learning
af: Das, Anindya, et al.
Udgivet: (2021)

Using deep learning algorithms to detect violent activities
af: Ammar, S.M. Rojin, et al.
Udgivet: (2019)

Weather Pattern Extraction using Statistical Methods & Machine Learning Techniques
af: Habib, Adria Binte
Udgivet: (2021)

Enhancing Monkeypox diagnosis: a machine learning approach for skin lession classification
af: Nazmee, Namirah, et al.
Udgivet: (2024)

Verifying online signatures through an iterative device independent model
af: Tahsin, Samiha, et al.
Udgivet: (2024)

Yield prediction for precision agriculture using extreme gradient boosting and support vector regression
af: Ahmed, Md. Sabbir, et al.
Udgivet: (2021)

Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
af: Oishi, Fayza Rezwana, et al.
Udgivet: (2020)

Detecting self-esteem level and depressive indication due to different parenting style using supervised learning techniques
af: Al Taawab, Abdullah, et al.
Udgivet: (2022)

Detection of fake identities on twitter using supervised machine learning
af: Rahman, MD. Takiur, et al.
Udgivet: (2019)