Interaction effect of process parameters and Pd‐electrocatalyst in formic acid electro‐oxidation for fuel cell applications: Implementing supervised machine learning algorithms

This publication has 49 references indexed in Scilit:

• Evaluation of support vector machine and artificial neural networks in weed detection using shape features
  Computers and Electronics in Agriculture, 2018
• Fe2P as a novel efficient catalyst promoter in Pd/C system for formic acid electro-oxidation in fuel cells reaction
  Journal of Power Sources, 2018
• Developing GPR model for forecasting the rock fragmentation in surface mines
  Engineering with Computers, 2017
• Tree-structured modelling of categorical predictors in generalized additive regression
  Advances in Data Analysis and Classification, 2017
• PdRu alloy nanoparticles of solid solution in atomic scale: outperformance towards formic acid electro-oxidation in acidic medium
  Electrochimica Acta, 2017
• Electrochemical hydrogen storage: Opportunities for fuel storage, batteries, fuel cells, and supercapacitors
  International Journal of Hydrogen Energy, 2017
• Direct liquid fuel cells: A review
  International Journal of Hydrogen Energy, 2017
• Gaussian Process Regression for Predictive But Interpretable Machine Learning Models: An Example of Predicting Mental Workload across Tasks
  Frontiers in Human Neuroscience, 2017
• A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model
  Energy, 2015
• Enhanced electrocatalytic oxidation of methanol on Pd/polypyrrole–graphene in alkaline medium
  Electrochimica Acta, 2011