مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

352
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

131
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

PREDICTION OF GAS/PARTICLE PARTITIONING COEFFICIENTS OF SEMI VOLATILE ORGANIC COMPOUNDS VIA QSPR METHODS: PC-ANN AND PLS ANALYSIS

Pages

  176-192

Abstract

 Linear and non-linear quantitative structure property relationship (QSPR) models for predicting the GAS/PARTICLE PARTITIONING COEFFICIENTs of SEMIVOLATILE ORGANIC COMPOUNDS were developed based on partial least squares (PLS) and artificial neural network (ANN) to identify a set of structurally based numerical descriptors. Multilinear regression (MLR) was used to build the linear QSPR models using combination of the compounds structural descriptors and topological indices related to environmental conditions such as temperature, pressure and particle size. The prediction results for PLS and ANN models give very good coefficient of determination (0.97). In consistent with experimental studies, it was shown that linear and non-linear regression analyses are useful tools to predict the relationship between the calculated descriptors and GAS/PARTICLE PARTITIONING COEFFICIENT.

Cites

  • No record.
  • References

  • No record.
  • Cite

    APA: Copy

    DEEB, O., KHADIKAR, P.V., & GOODARZI, M.. (2011). PREDICTION OF GAS/PARTICLE PARTITIONING COEFFICIENTS OF SEMI VOLATILE ORGANIC COMPOUNDS VIA QSPR METHODS: PC-ANN AND PLS ANALYSIS. JOURNAL OF THE IRANIAN CHEMICAL SOCIETY(JICS), 8(1), 176-192. SID. https://sid.ir/paper/282512/en

    Vancouver: Copy

    DEEB O., KHADIKAR P.V., GOODARZI M.. PREDICTION OF GAS/PARTICLE PARTITIONING COEFFICIENTS OF SEMI VOLATILE ORGANIC COMPOUNDS VIA QSPR METHODS: PC-ANN AND PLS ANALYSIS. JOURNAL OF THE IRANIAN CHEMICAL SOCIETY(JICS)[Internet]. 2011;8(1):176-192. Available from: https://sid.ir/paper/282512/en

    IEEE: Copy

    O. DEEB, P.V. KHADIKAR, and M. GOODARZI, “PREDICTION OF GAS/PARTICLE PARTITIONING COEFFICIENTS OF SEMI VOLATILE ORGANIC COMPOUNDS VIA QSPR METHODS: PC-ANN AND PLS ANALYSIS,” JOURNAL OF THE IRANIAN CHEMICAL SOCIETY(JICS), vol. 8, no. 1, pp. 176–192, 2011, [Online]. Available: https://sid.ir/paper/282512/en

    Related Journal Papers

  • No record.
  • Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    Move to top
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button