March 29, 2022 article Open access Predicting octane numbers relying on principal component analysis and artificial neural network Computers & Chemical Engineering DOI: 10.1016/j.compchemeng.2022.107784 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 14 References 2 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Using machine learning with target-specific feature sets for structure-property relationship modeling of octane numbers and octane sensitivity 2020 Fuel article Chemical Engineering Advanced Combustion Engine Technologies 60 citations Analysis of Turbulent Reacting Jets via Principal Component Analysis 2020 Springer eBooks book-chapter Physics and Astronomy Model Reduction and Neural Networks 7 citations 2 results