BCOVIDOA: A Novel Binary Coronavirus Disease Optimization Algorithm for Feature Selection

[1]  Asmaa M. Khalid,et al.  COVIDOA: a novel evolutionary optimization algorithm based on coronavirus disease replication lifecycle , 2022, Neural Computing and Applications.

[2]  Nageswara Rao Eluri,et al.  Cancer data classification by quantum-inspired immune clone optimization-based optimal feature selection using gene expression data: deep learning approach , 2021, Data Technol. Appl..

[3]  Chandra Sekhara Rao Annavarapu,et al.  Clustering-based hybrid feature selection approach for high dimensional microarray data , 2021 .

[4]  Amir H. Gandomi,et al.  The Arithmetic Optimization Algorithm , 2021, Computer Methods in Applied Mechanics and Engineering.

[5]  M. Khan,et al.  Comparative genome analysis of novel coronavirus (SARS-CoV-2) from different geographical locations and the effect of mutations on major target proteins: An in silico insight , 2020, PloS one.

[6]  K. Keeling,et al.  Pharmacological approaches for targeting cystic fibrosis nonsense mutations. , 2020, European journal of medicinal chemistry.

[7]  Pei Hu,et al.  Improved Binary Grey Wolf Optimizer and Its application for feature selection , 2020, Knowl. Based Syst..

[8]  M. Pascual.  Coronavirus SARS-CoV-2: Analysis of subgenomic mRNA transcription, 3CLpro and PL2pro protease cleavage sites and protein synthesis , 2020, 2004.00746.

[9]  Rob Phillips,et al.  SARS-CoV-2 (COVID-19) by the numbers , 2020, eLife.

[10]  Abdul Rahim Abdullah,et al.  A New Quadratic Binary Harris Hawk Optimization for Feature Selection , 2019, Electronics.

[11]  Feng Jiang,et al.  A cross-domain collaborative filtering algorithm with expanding user and item features via the latent factor space of auxiliary domains , 2019, Pattern Recognit..

[12]  Hossam Faris,et al.  Feature selection using binary grey wolf optimizer with elite-based crossover for Arabic text classification , 2019, Neural Computing and Applications.

[13]  Said Jadid Abdul Kadir,et al.  Binary Optimization Using Hybrid Grey Wolf Optimization for Feature Selection , 2019, IEEE Access.

[14]  Siddhartha Bhattacharyya,et al.  S-shaped Binary Whale Optimization Algorithm for Feature Selection , 2019 .

[15]  Jaime Lloret,et al.  Intelligent IoT Traffic Classification Using Novel Search Strategy for Fast-Based-Correlation Feature Selection in Industrial Environments , 2018, IEEE Internet of Things Journal.

[16]  Xu Yu,et al.  SVMs Classification Based Two-side Cross Domain Collaborative Filtering by inferring intrinsic user and item features , 2018, Knowl. Based Syst..

[17]  Xiangjun Dong,et al.  An Industrial Internet of Things Feature Selection Method Based on Potential Entropy Evaluation Criteria , 2018, IEEE Access.

[18]  Majdi M. Mafarja,et al.  Hybrid Whale Optimization Algorithm with simulated annealing for feature selection , 2017, Neurocomputing.

[19]  Majdi M. Mafarja,et al.  Binary Dragonfly Algorithm for Feature Selection , 2017, 2017 International Conference on New Trends in Computing Sciences (ICTCS).

[20]  Pornpit Wongthongtham,et al.  Big Data Challenges for the Internet of Things (IoT) Paradigm , 2017 .

[21]  J. Ioannidis,et al.  When Null Hypothesis Significance Testing Is Unsuitable for Research: A Reassessment , 2016, bioRxiv.

[22]  Heiko Wersing,et al.  KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift , 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

[23]  Yohei Yamauchi,et al.  Principles of Virus Uncoating: Cues and the Snooker Ball , 2016, Traffic.

[24]  Aboul Ella Hassanien,et al.  Binary grey wolf optimization approaches for feature selection , 2016, Neurocomputing.

[25]  Hossein Nezamabadi-pour,et al.  An advanced ACO algorithm for feature subset selection , 2015, Neurocomputing.

[26]  Xin-She Yang,et al.  Binary Flower Pollination Algorithm and Its Application to Feature Selection , 2015, Recent Advances in Swarm Intelligence and Evolutionary Computation.

[27]  Ferat Sahin,et al.  A survey on feature selection methods , 2014, Comput. Electr. Eng..

[28]  H. Pedrini,et al.  Data feature selection based on Artificial Bee Colony algorithm , 2013, EURASIP J. Image Video Process..

[29]  Xin-She Yang,et al.  BCS: A Binary Cuckoo Search algorithm for feature selection , 2013, 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013).

[30]  Andrew Lewis,et al.  S-shaped versus V-shaped transfer functions for binary Particle Swarm Optimization , 2013, Swarm Evol. Comput..

[31]  Long Jin,et al.  A novel hybrid Genetic Algorithm and Simulated Annealing for feature selection and kernel optimization in support vector regression , 2012, 2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI).

[32]  Xin-She Yang,et al.  BBA: A Binary Bat Algorithm for Feature Selection , 2012, 2012 25th SIBGRAPI Conference on Graphics, Patterns and Images.

[33]  Kazuyuki Murase,et al.  A new local search based hybrid genetic algorithm for feature selection , 2011, Neurocomputing.

[34]  Francisco Herrera,et al.  A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms , 2011, Swarm Evol. Comput..

[35]  Kewei Cheng,et al.  Feature Selection , 2016, ACM Comput. Surv..

[36]  El-Ghazali Talbi,et al.  Hybridizing exact methods and metaheuristics: A taxonomy , 2009, Eur. J. Oper. Res..

[37]  Yan Dong,et al.  Feature Selection with Discrete Binary Differential Evolution , 2009, 2009 International Conference on Artificial Intelligence and Computational Intelligence.

[38]  Ke Huang,et al.  Wavelet Feature Selection for Image Classification , 2008, IEEE Transactions on Image Processing.

[39]  Rafael Bello,et al.  Two-Step Particle Swarm Optimization to Solve the Feature Selection Problem , 2007, Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007).

[40]  Xiaoming Xu,et al.  A hybrid genetic algorithm for feature selection wrapper based on mutual information , 2007, Pattern Recognit. Lett..

[41]  Pedro Larrañaga,et al.  A review of feature selection techniques in bioinformatics , 2007, Bioinform..

[42]  John F. Atkins,et al.  Ribosomal frameshifting in decoding antizyme mRNAs from yeast and protists to humans: close to 300 cases reveal remarkable diversity despite underlying conservation , 2007, Nucleic acids research.

[43]  Jacob Zahavi,et al.  Using simulated annealing to optimize the feature selection problem in marketing applications , 2006, Eur. J. Oper. Res..

[44]  Li-Ping Jing,et al.  Improved feature selection approach TFIDF in text mining , 2002, Proceedings. International Conference on Machine Learning and Cybernetics.

[45]  Catherine Blake,et al.  UCI Repository of machine learning databases , 1998 .

[46]  Huan Liu,et al.  Feature Selection for Classification , 1997, Intell. Data Anal..

[47]  N. Altman.  An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression , 1992 .