Godinho, A.;                     Fernandes, D.;                     Soares, G.;                     Pina, P.;                     Sebastião, P.;                     Correia, A.;                     Ferreira, L.S.    
        A Novel Way to Automatically Plan Cellular Networks Supported by Linear Programming and Cloud Computing. Appl. Sci. 2020, 10, 3072.
    https://doi.org/10.3390/app10093072
    AMA Style
    
                                Godinho A,                                 Fernandes D,                                 Soares G,                                 Pina P,                                 Sebastião P,                                 Correia A,                                 Ferreira LS.        
                A Novel Way to Automatically Plan Cellular Networks Supported by Linear Programming and Cloud Computing. Applied Sciences. 2020; 10(9):3072.
        https://doi.org/10.3390/app10093072
    
    Chicago/Turabian Style
    
                                Godinho, André,                                 Daniel Fernandes,                                 Gabriela Soares,                                 Paulo Pina,                                 Pedro Sebastião,                                 Américo Correia,                                 and Lucio S. Ferreira.        
                2020. "A Novel Way to Automatically Plan Cellular Networks Supported by Linear Programming and Cloud Computing" Applied Sciences 10, no. 9: 3072.
        https://doi.org/10.3390/app10093072
    
    APA Style
    
                                Godinho, A.,                                 Fernandes, D.,                                 Soares, G.,                                 Pina, P.,                                 Sebastião, P.,                                 Correia, A.,                                 & Ferreira, L. S.        
        
        (2020). A Novel Way to Automatically Plan Cellular Networks Supported by Linear Programming and Cloud Computing. Applied Sciences, 10(9), 3072.
        https://doi.org/10.3390/app10093072