Prediction of lattice constant of pyrochlore compounds using optimized machine learning model

QR Code

Prediction of lattice constant of pyrochlore compounds using optimized machine learning model

The pyrochlore compounds has a general formula of A2 under cubic structure and have been identified as a good catalyst for production of clean energy due to its unique physical properties. In this study, we used an optimized machine learning technique based on Particle Swarm Optimization-Support Vec...

Full description

Bibliographic Details
Main Authors:	Mohamad Zamri, Isma Uzayr, Abd Rahman, Mohd Amiruddin, Bundak, Caceja Elyca
Format:	Article
Published:	Springer Nature 2023
Online Access:	http://psasir.upm.edu.my/id/eprint/110082/

Similar Items

Prediction of the lattice constants of pyrochlore compounds using machine learning
by: Alade, Ibrahim Olanrewaju, et al.
Published: (2022)

Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
by: Bundak, Caceja Elyca
Published: (2021)

Analysis of multiple prediction techniques of received signal strength to reduce surveying effort in indoor positioning
by: Abd Rahman, Mohd Amiruddin, et al.
Published: (2022)

Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework
by: Aidil Zulkafli, Nadhirah, et al.
Published: (2024)

Perovskite lattice constant prediction framework using optimized artificial neural network and fuzzy logic models by metaheuristic algorithms
by: Bouzateur, Inas, et al.
Published: (2023)

Fuzzy rank cluster top k Euclidean distance and triangle based algorithm for magnetic field indoor positioning system
by: Bundak, Caceja Elyca, et al.
Published: (2021)

Effect of different signal weighting function of magnetic field using KNN for indoor localization
by: Bundak, Caceja Elyca, et al.
Published: (2022)

Prediction of blood-brain barrier permeability of compounds by machine learning algorithms
by: Feng, Tan wei, et al.
Published: (2024)

Preparation and Characterisation of Bismuth Zinc Tantalate Pyrochlore Materials
by: Khaw, Chwin Chieh
Published: (2007)

Structural and electrical properties of bismuth magnesium tantalate pyrochlores.
by: Tan, P. Y., et al.
Published: (2012)

Dielectric pyrochlores in bismuth magnesium tantalate ternary system
by: Tan, Kar Ban, et al.
Published: (2012)

Predicting the classification of heart failure patients using optimized machine learning algorithms
by: Ahmed, Marzia, et al.
Published: (2025)

Synthesis and electrical properties of Zn-substituted bismuth copper tantalate pyrochlores
by: Chon, Mun Ping, et al.
Published: (2016)

Electrical circuit modeling for the relaxor response of bismuth magnesium tantalate pyrochlore
by: Tan, P.Y., et al.
Published: (2024)

Investigation of structural and dielectric properties of subsolidus bismuth iron niobate pyrochlores
by: Jusoh, Farah Aishah, et al.
Published: (2020)

Constant Frequency Torque Controller for DTC with Multilevel Inverter of Induction Machines
by: Norjulia, Mohamad Nordin, et al.
Published: (2016)

Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
by: almahameed, Bader aldeen, et al.
Published: (2024)

Additive manufacturing process optimization for complex lattice design architecture
by: Mazlan, Siti Nur Humaira, et al.
Published: (2020)

Catalytic combustion of methane over cobalt doped lanthanum stannate pyrochlore oxide
by: Cheng, J., et al.
Published: (2008)

Radiation tolerance of ceramics—insights from atomistic simulation of damage accumulation in pyrochlores
by: Devanathan, R., et al.
Published: (2010)

Subsolidus solution and electrical properties of Sr-substituted bismuth magnesium niobate pyrochlores
by: Mat Dasin, Nurul Aidayu, et al.
Published: (2017)

Doping mechanisms and impedance study of Ba-substituted bismuth magnesium niobate pyrochlores
by: Mat Dasin, Nurul Aidayu, et al.
Published: (2019)

Doping mechanisms and dielectric properties of Ca-doped bismuth magnesium niobate pyrochlores
by: Mat Dasin, Nurul Aidayu, et al.
Published: (2020)

Novel pyrochlore-structured bismuth iron antimonates: structural, impedance and electrochemical studies
by: Jusoh, F. A., et al.
Published: (2021)

Application Of Lattice Boltzmann Method In Predicting Flow Of Shear Driven Cavities
by: Abdul Munir, Fudhail, et al.
Published: (2011)

Constant frequency torque and flux controllers for direct torque control of induction machines
by: Nik Idris, Nik Rumzi, et al.
Published: (2003)

Constant frequency torque and flux controllers for direct torque control of induction machines
by: Idris, N. R. N., et al.
Published: (2003)

Optimization-driven extreme learning machine for floating photovoltaic power prediction: A teaching learning-based approach
by: Mohd Redzuan, Ahmad, et al.
Published: (2025)

Optimization of machine learning models for predicting glutinous rice quality stored under various conditions
by: Dasore, Abhishek, et al.
Published: (2025)

The analysis on effect of thrust constant, spring constant, electrical time constant, mechanical time constant to oscillation displacement of slot-less linear oscillatory actuator
by: Misron, Norhisam, et al.
Published: (2008)

Atomistic Simulations of Ceramic Materials Relevant for Nuclear Waste Management: Cases of Monazlte and Pyrochlore
by: Li, Y., et al.
Published: (2016)

A Rietveld refinement approach in structural study of bismuth zinc niobate cubic pyrochlores
by: Tan, Kar Ban, et al.
Published: (2010)

High temperature impedance spectroscopy study of non-stoichiometric bismuth zinc niobate pyrochlore.
by: Tan, Kar Ban, et al.
Published: (2009)

Bitcoin price prediction using machine learning
by: Tang, Jian Yang
Published: (2023)

Diabetic Retinopathy Prediction Using Machine Learning
by: Ravikiran, Y., et al.
Published: (2024)

Cancer recurrence prediction using machine learning
by: Shoon Lei, Win, et al.
Published: (2014)

Crime rate prediction using machine learning
by: Chee, Man Hang
Published: (2022)

Machine learning approach for flood risks prediction
by: Razali, Nazim, et al.
Published: (2020)

Earthquake prediction model based on geomagnetic field data using automated machine learning
by: Yusof, Khairul Adib, et al.
Published: (2024)

The Combinatorics of Lattice Polytopes
by: Hall, Thomas
Published: (2024)