Prediction of thermophysical properties for binary mixtures of common ionic liquids with water or alcohol at several temperatures and atmospheric pressure by means of artificial neural network

Industrial and Engineering Chemistry Research

Volumn 53, Issue 17, 2014, Pages 7247-7262

  Golzar, Karim ^a   Amjad Iranagh, Sepideh ^a   Modarress, Hamid ^a  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERIC PRESSURE; FORECASTING; IONIC LIQUIDS; NEURAL NETWORKS; PROPANOL; REFRACTIVE INDEX; THERMODYNAMIC PROPERTIES; VISCOSITY;

DYNAMIC VISCOSITIES; EXCESS MOLAR VOLUMES; INPUT PARAMETER; IONIC LIQUID (ILS); MOLE FRACTION; PREDICTION ERRORS; PURE COMPONENTS; STATISTICAL QUALITY;

BINARY MIXTURES;

EID: 84899667451     PISSN: 08885885     EISSN: 15205045     Source Type: Journal    
DOI: 10.1021/ie5007432     Document Type: Article

References (94)

1. Królikowska, M.; Karpińska, M.; Zawadzki, M. Phase equilibria study of (ionic liquid+water) binary mixtures Fluid Phase Equilib. 2013, 354 (0) 66-74
2. Wlaz?o, M.; Marciniak, A. Ternary liquid-liquid equilibria of trifluorotris(perfluoroethyl)phosphate based ionic liquids+methanol+heptane Fluid Phase Equilib. 2013, 338 (0) 253-256
3. Hwang, I. C.; Park, S. J.; Kwon, R. H. Liquid-liquid equilibria for ternary mixtures of methyl tert-amyl ether+methanol (or ethanol)+imidazolium- based ionic liquids at 298.15K Fluid Phase Equilib. 2012, 316 (0) 11-16
4. Shin, S. H.; Hwang, I.-C.; Park, S.-J. Liquid-liquid equilibria at 298.15K for ternary mixtures of methyl tert-butyl ether+methanol (or ethanol)+imidazolium-based ionic liquids at atmospheric pressure Fluid Phase Equilib. 2013, 342 (0) 82-87
5. Keshavarz, L.; Javanmardi, J.; Eslamimanesh, A.; Mohammadi, A. H. Experimental measurement and thermodynamic modeling of methane hydrate dissociation conditions in the presence of aqueous solution of ionic liquid Fluid Phase Equilib. 2013, 354 (0) 312-318
6. Rehák, K.; Morávek, P.; Strejc, M. Determination of mutual solubilities of ionic liquids and water Fluid Phase Equilib. 2012, 316 (0) 17-25
7. Shiflett, M. B.; Elliott, B. A.; Yokozeki, A. Phase behavior of vinyl fluoride in room-temperature ionic liquids [emim][Tf2N], [bmim][N(CN)2], [bmpy][BF4], [bmim][HFPS] and [omim][TFES] Fluid Phase Equilib. 2012, 316 (0) 147-155
8. Cai, F.; Wu, X.; Chen, C.; Chen, X.; Asumana, C.; Haque, M. R.; Yu, G. Isobaric vapor-liquid equilibrium for methanol+dimethyl carbonate+phosphoric- based ionic liquids Fluid Phase Equilib. 2013, 352 (0) 47-53
9. Ravilla, U. K.; Banerjee, T. Liquid liquid equilibria of imidazolium based ionic liquid+pyridine+hydrocarbon at 298.15K: Experiments and correlations Fluid Phase Equilib. 2012, 324 (0) 17-27
10. Santos, S. I.; Bogel-?ukasik, E.; Bogel-?ukasik, R. The ionic liquid effect on solubility of aniline, a simple aromatic amine: Perspective of solvents' mixture Fluid Phase Equilib. 2012, 325 (0) 105-110
11. Seiler, M.; Kühn, A.; Ziegler, F.; Wang, X. Sustainable Cooling Strategies Using New Chemical System Solutions Ind. Eng. Chem. Res. 2013, 52 (47) 16519-16546
12. Casas, A.; Oliet, M.; Alonso, M. V.; Santos, T. M.; Rodriguez, F. Dissolution of Pinus radiata and Eucalyptus Globulus Woods in 1-Allyl-3-methylimidazolium Chloride for Cellulose or Lignin Regeneration Ind. Eng. Chem. Res. 2013, 52 (10) 3628-3636
13. Marsh, K. N.; Boxall, J. A.; Lichtenthaler, R. Room temperature ionic liquids and their mixtures-a review Fluid Phase Equilib. 2004, 219 (1) 93-98
14. Chin, H.-Y.; Lee, B.-S.; Chen, Y.-P.; Chen, P.-C.; Lin, S.-T.; Chen, L.-J. Prediction of Phase Equilibrium of Methane Hydrates in the Presence of Ionic Liquids Ind. Eng. Chem. Res. 2013, 52 (47) 16985-16992
15. MacFarlane, D. R.; Meakin, P.; Sun, J.; Amini, N.; Forsyth, M. Pyrrolidinium Imides: A New Family of Molten Salts and Conductive Plastic Crystal Phases J.Phys. Chem. B 1999, 103 (20) 4164-4170
16. McEwen, A. B.; Ngo, H. L.; LeCompte, K.; Goldman, J. L. Electrochemical Properties of Imidazolium Salt Electrolytes for Electrochemical Capacitor Applications J. Electrochem. Soc. 1999, 146 (5) 1687-1695
17. Matsumoto, H.; Yanagida, M.; Tanimoto, K.; Nomura, M.; Kitagawa, Y.; Miyazaki, Y. Highly Conductive Room Temperature Molten Salts Based on Small Trimethylalkylammonium Cations and Bis(trifluoromethylsulfonyl)imide Chem. Lett. 2000, 29 (8) 922-923
18. Ghatee, M. H.; Bahrami, M.; Khanjari, N. Measurement and study of density, surface tension, and viscosity of quaternary ammonium-based ionic liquids ([N222(n)]Tf2N) J. Chem. Thermodyn. 2013, 65 (0) 42-52
19. Ue, M.; Takeda, M.; Toriumi, A.; Kominato, A.; Hagiwara, R.; Ito, Y. Application of Low-Viscosity Ionic Liquid to the Electrolyte of Double-Layer Capacitors J. Electrochem. Soc. 2003, 150 (4) A499-A502
20. Sato, T.; Masuda, G.; Takagi, K. Electrochemical properties of novel ionic liquids for electric double layer capacitor applications Electrochim. Acta 2004, 49 (21) 3603-3611
21. 2 cell using room temperature ionic liquids (RTILs) based on quaternary ammonium cation-Effect of the structure J. Power Sources 2005, 146 (1-2) 693-697
22. 2 cell with low-viscosity ionic liquids based on bis(fluorosulfonyl)imide [FSI]- J. Power Sources 2006, 160 (2) 1308-1313
23. Kawano, R.; Matsui, H.; Matsuyama, C.; Sato, A.; Susan, M. A. B. H.; Tanabe, N.; Watanabe, M. High performance dye-sensitized solar cells using ionic liquids as their electrolytes J. Photochem. Photobiol., A 2004, 164 (1-3) 87-92
24. Mikoshiba, S.; Murai, S.; Sumino, H.; Kado, T.; Kosugi, D.; Hayase, S. Ionic liquid type dye-sensitized solar cells: increases in photovoltaic performances by adding a small amount of water Current Appl. Phys. 2005, 5 (2) 152-158
25. 2 Capture and Comparisons to Imidazolium-Based Ionic Liquids Ind. Eng. Chem. Res. 2011, 50 (14) 8665-8677
26. Liu, H.; Zhang, Y.; Yao, H.; Yu, D.; Zhao, W.; Bai, X. Improving Mass Transfer in Gas-Liquid by Ionic Liquids Dispersion J. Dispersion Sci. Technol. 2012, 33 (12) 1723-1729
27. Singh, M. P.; Singh, R. K. Correlation between ultrasonic velocity, surface tension, density and viscosity of ionic liquids Fluid Phase Equilib. 2011, 304 (1-2) 1-6
28. Ferreira, C. E.; Talavera-Prieto, N. M. C.; Fonseca, I. M. A.; Portugal, A. T. G.; Ferreira, A. G. M. Measurements of pVT, viscosity, and surface tension of trihexyltetradecylphosphonium tris(pentafluoroethyl)trifluorophosphate ionic liquid and modelling with equations of state J. Chem. Thermodyn. 2012, 47 (0) 183-196
29. Domańska, U.; Zawadzki, M.; Lewandrowska, A. Effect of temperature and composition on the density, viscosity, surface tension, and thermodynamic properties of binary mixtures of N-octylisoquinolinium bis{(trifluoromethyl) sulfonyl}imide with alcohols J. Chem. Thermodyn. 2012, 48 (0) 101-111
30. Paul, S.; Panda, A. K. Physicochemical investigations on the aqueous solution of an ionic liquid, 1-butyl-3-methylimidazolium methanesulfonate, [bmim][MS], in a concentrated and dilute regime Colloids Surf., A 2012, 404 (0) 1-11
31. Troncoso, J.; Cerdeiriña, C. A.; Sanmamed, Y. A.; Romaní, L.; Rebelo, L. P. N. Thermodynamic Properties of Imidazolium-Based Ionic Liquids: Densities, Heat Capacities, and Enthalpies of Fusion of [bmim][PF6] and [bmim][NTf2] J. Chem. Eng. Data 2006, 51 (5) 1856-1859
32. Nieto de Castro, C. A.; Langa, E.; Morais, A. L.; Lopes, M. L. M.; Lourenço, M. J. V.; Santos, F. J. V.; Santos, M. S. C. S.; Lopes, J. N. C.; Veiga, H. I. M.; Macatrão, M.; Esperança, J. M. S. S.; Marques, C. S.; Rebelo, L. P. N.; Afonso, C. A. M. Studies on the density, heat capacity, surface tension and infinite dilution diffusion with the ionic liquids [C4mim][NTf2], [C4mim][dca], [C2mim][EtOSO3] and [Aliquat][dca] Fluid Phase Equilib. 2010, 294 (1-2) 157-179
33. Diogo, J. C. F.; Caetano, F. J. P.; Fareleira, J. M. N. A.; Wakeham, W. A. Viscosity measurements of three ionic liquids using the vibrating wire technique Fluid Phase Equilib. 2013, 353 (0) 76-86
34. Tariq, M.; Carvalho, P. J.; Coutinho, J. A. P.; Marrucho, I. M.; Lopes, J. N. C.; Rebelo, L. P. N. Viscosity of (C2-C14) 1-alkyl-3-methylimidazolium bis(trifluoromethylsulfonyl)amide ionic liquids in an extended temperature range Fluid Phase Equilib. 2011, 301 (1) 22-32
35. Gómez, E.; González, B.; Domínguez, á.; Tojo, E.; Tojo, J. Dynamic Viscosities of a Series of 1-Alkyl-3-methylimidazolium Chloride Ionic Liquids and Their Binary Mixtures with Water at Several Temperatures J. Chem. Eng. Data 2006, 51 (2) 696-701
36. González, E. J.; González, B.; Calvar, N.; Domínguez, á. Physical Properties of Binary Mixtures of the Ionic Liquid 1-Ethyl-3-methylimidazolium Ethyl Sulfate with Several Alcohols at T = (298.15, 313.15, and 328.15) K and Atmospheric Pressure J. Chem. Eng. Data 2007, 52 (5) 1641-1648
37. González, B. a.; Calvar, N.; Gómez, E.; Macedo, E. n. A.; Domínguez, A. n. Synthesis and Physical Properties of 1-Ethyl 3-methylpyridinium Ethylsulfate and Its Binary Mixtures with Ethanol and Water at Several Temperatures J. Chem. Eng. Data 2008, 53 (8) 1824-1828
38. Rodríguez, H.; Brennecke, J. F. Temperature and Composition Dependence of the Density and Viscosity of Binary Mixtures of Water + Ionic Liquid J. Chem. Eng. Data 2006, 51 (6) 2145-2155
39. González, B.; Calvar, N.; Gómez, E.; Domínguez, á. Physical properties of the ternary system (ethanol+water+1-butyl-3- methylimidazolium methylsulphate) and its binary mixtures at several temperatures J. Chem. Thermodyn. 2008, 40 (8) 1274-1281
40. Quijada-Maldonado, E.; van der Boogaart, S.; Lijbers, J. H.; Meindersma, G. W.; de Haan, A. B. Experimental densities, dynamic viscosities and surface tensions of the ionic liquids series 1-ethyl-3-methylimidazolium acetate and dicyanamide and their binary and ternary mixtures with water and ethanol at T=298.15 to 343.15K J. Chem. Thermodyn. 2012, 51 (0) 51-58
41. Rilo, E.; Vila, J.; Pico, J.; García-Garabal, S.; Segade, L.; Varela, L. M.; Cabeza, O. Electrical Conductivity and Viscosity of Aqueous Binary Mixtures of 1-Alkyl-3-methyl Imidazolium Tetrafluoroborate at Four Temperatures J. Chem. Eng. Data 2009, 55 (2) 639-644
42. 2 Bubble Behavior in Ionic Liquid Systems Ind. Eng. Chem. Res. 2013, 53 (1) 428-439
43. Torrecilla, J. S.; Tortuero, C.; Cancilla, J. C.; Díaz- Rodríguez, P. Estimation with neural networks of the water content in imidazolium-based ionic liquids using their experimental density and viscosity values Talanta 2013, 113 (0) 93-98
44. Shojaee, S. A.; Farzam, S.; Hezave, A. Z.; Lashkarbolooki, M.; Ayatollahi, S. A new correlation for estimating thermal conductivity of pure ionic liquids Fluid Phase Equilib. 2013, 354 (0) 199-206
45. Matsuda, H.; Yamamoto, H.; Kurihara, K.; Tochigi, K. Computer-aided reverse design for ionic liquids by QSPR using descriptors of group contribution type for ionic conductivities and viscosities Fluid Phase Equilib. 2007, 261 (1-2) 434-443
46. Lashkarbolooki, M.; Hezave, A. Z.; Ayatollahi, S. Artificial neural network as an applicable tool to predict the binary heat capacity of mixtures containing ionic liquids Fluid Phase Equilib. 2012, 324 (0) 102-107
47. Han, C.; Yu, G.; Wen, L.; Zhao, D.; Asumana, C.; Chen, X. Data and QSPR study for viscosity of imidazolium-based ionic liquids Fluid Phase Equilib. 2011, 300 (1-2) 95-104
48. Hezave, A. Z.; Lashkarbolooki, M.; Raeissi, S. Using artificial neural network to predict the ternary electrical conductivity of ionic liquid systems Fluid Phase Equilib. 2012, 314 (0) 128-133
49. Chen, B.-K.; Liang, M.-J.; Wu, T.-Y.; Wang, H. P. A high correlate and simplified QSPR for viscosity of imidazolium-based ionic liquids Fluid Phase Equilib. 2013, 350 (0) 37-42
50. Hezave, A. Z.; Raeissi, S.; Lashkarbolooki, M. Estimation of Thermal Conductivity of Ionic Liquids Using a Perceptron Neural Network Ind. Eng. Chem. Res. 2012, 51 (29) 9886-9893
51. Sattari, M.; Gharagheizi, F.; Ilani-Kashkouli, P.; Mohammadi, A. H.; Ramjugernath, D. Estimation of the Heat Capacity of Ionic Liquids: A Quantitative Structure-Property Relationship Approach Ind. Eng. Chem. Res. 2013, 52 (36) 13217-13221
52. Valderrama, J. O.; Reátegui, A.; Rojas, R. E. Density of Ionic Liquids Using Group Contribution and Artificial Neural Networks Ind. Eng. Chem. Res. 2009, 48 (6) 3254-3259
53. Safamirzaei, M.; Modarress, H. Application of neural network molecular modeling for correlating and predicting Henry's law constants of gases in [bmim][PF6] at low pressures Fluid Phase Equilib. 2012, 332 (0) 165-172
54. Golzar, K.; Amjad-Iranagh, S.; Modarress, H. Prediction of density, surface tension and viscosity of quaternary ammonium-based ionic liquids ([N222(n)]Tf2N) by means of artificial intelligence techniques. J. Dispersion Sci. Technol. 2014, DOI: 10.1080/01932691.2013.879533.
55. Mohanty, S. Estimation of vapour liquid equilibria of binary systems, carbon dioxide-ethyl caproate, ethyl caprylate and ethyl caprate using artificial neural networks Fluid Phase Equilib. 2005, 235 (1) 92-98
56. Nguyen, V. D.; Tan, R. R.; Brondial, Y.; Fuchino, T. Prediction of vapor-liquid equilibrium data for ternary systems using artificial neural networks Fluid Phase Equilib. 2007, 254 (1-2) 188-197
57. Ahmadi, M. A. Neural network based unified particle swarm optimization for prediction of asphaltene precipitation Fluid Phase Equilib. 2012, 314 (0) 46-51
58. Nasouri, K.; Bahrambeygi, H.; Rabbi, A.; Shoushtari, A. M.; Kaflou, A. Modeling and optimization of electrospun PAN nanofiber diameter using response surface methodology and artificial neural networks J. Appl. Polym. Sci. 2012, 126 (1) 127-135
59. Sresungsuwan, N.; Hansupalak, N. Prediction of mechanical properties of compatibilized styrene/natural-rubber blend by using reaction conditions: Central composite design vs. artificial neural networks J. Appl. Polym. Sci. 2013, 127 (1) 356-365
60. Fazilat, H.; Akhlaghi, S.; Shiri, M. E.; Sharif, A. Predicting thermal degradation kinetics of nylon6/feather keratin blends using artificial intelligence techniques Polymer 2012, 53 (11) 2255-2264
61. Samavati, V.; Emam-Djomeh, Z.; Omid, M. Prediction of Rheological Properties of Multi-Component Dispersions by Using Artificial Neural Networks J. Dispersion Sci. Technol. 2014, 35 (3) 428-434
62. Lashkarbolooki, M.; Mowla, D.; Esmaeilzadeh, F. Artificial Neural Network Modeling of Deposition Thickness Through the Pipeline J. Dispersion Sci. Technol. 2012, 34 (4) 496-503
63. Nasiri, H. G.; Mosavian, M. T. H.; Kadkhodaee, R.; Sargolzae, J. Modeling of Oil-Water Emulsion Separation in Ultrasound Standing Wavefield by Neural Network J. Dispersion Sci. Technol. 2012, 34 (4) 490-495
64. Asoodeh, M.; Gholami, A.; Bagheripour, P. Oil-CO2MMP Determination in Competition of Neural Network, Support Vector Regression, and Committee Machine J. Dispersion Sci. Technol. 2013, 35 (4) 564-571
65. Khajeh, A.; Modarress, H. Quantitative Structure-Property Relationship Prediction of Liquid Heat Capacity at 298.15 K for Organic Compounds Ind. Eng. Chem. Res. 2012, 51 (17) 6251-6255
66. Khajeh, A.; Modarress, H. Quantitative Structure-Property Relationship Prediction of Gas Heat Capacity for Organic Compounds Ind. Eng. Chem. Res. 2012, 51 (41) 13490-13495
67. Khajeh, A.; Modarress, H. Quantitative Structure-Property Relationship for Flash Points of Alcohols Ind. Eng. Chem. Res. 2011, 50 (19) 11337-11342
68. Kamari, A.; Khaksar-Manshad, A.; Gharagheizi, F.; Mohammadi, A. H.; Ashoori, S. Robust Model for the Determination of Wax Deposition in Oil Systems Ind. Eng. Chem. Res. 2013, 52 (44) 15664-15672
69. Díaz-Rodríguez, P.; Cancilla, J. C.; Matute, G.; Torrecilla, J. S. Determination of Physicochemical Properties of Pyridinium-Based Ionic Liquid Binary Mixtures with a Common Component through Neural Networks Ind. Eng. Chem. Res. 2013, 53 (2) 1015-1019
70. Safamirzaei, M.; Modarress, H. Hydrogen solubility in heavy n-alkanes; modeling and prediction by artificial neural network Fluid Phase Equilib. 2011, 310 (1-2) 150-155
71. 2 in common polymers Measurement 2013, 46 (10) 4206-4225
72. Golzar, K.; Jalali-Arani, A.; Nematollahi, M. Statistical investigation on physical-mechanical properties of base and polymer modified bitumen using Artificial Neural Network Constr. Build. Mater. 2012, 37 (0) 822-831
73. Faúndez, C. A.; Quiero, F. A.; Valderrama, J. O. Phase equilibrium modeling in ethanol+congener mixtures using an artificial neural network Fluid Phase Equilib. 2010, 292 (1-2) 29-35
74. Yamamoto, H.; Tochigi, K. Prediction of vapor-liquid equilibria using reconstruction-learning neural network method Fluid Phase Equilib. 2007, 257 (2) 169-172
75. He, X.; Zhang, X.; Zhang, S.; Liu, J.; Li, C. Prediction of phase equilibrium properties for complicated macromolecular systems by HGALM neural networks Fluid Phase Equilib. 2005, 238 (1) 52-57
76. Urata, S.; Takada, A.; Murata, J.; Hiaki, T.; Sekiya, A. Prediction of vapor-liquid equilibrium for binary systems containing HFEs by using artificial neural network Fluid Phase Equilib. 2002, 199 (1-2) 63-78
77. Karimi, H.; Yousefi, F. Application of artificial neural network-genetic algorithm (ANN-GA) to correlation of density in nanofluids Fluid Phase Equilib. 2012, 336 (0) 79-83
78. Eslamimanesh, A.; Gharagheizi, F.; Illbeigi, M.; Mohammadi, A. H.; Fazlali, A.; Richon, D. Phase equilibrium modeling of clathrate hydrates of methane, carbon dioxide, nitrogen, and hydrogen+water soluble organic promoters using Support Vector Machine algorithm Fluid Phase Equilib. 2012, 316 (0) 34-45
79. Laugier, S.; Richon, D. Use of artificial neural networks for calculating derived thermodynamic quantities from volumetric property data Fluid Phase Equilib. 2003, 210 (2) 247-255
80. Lashkarbolooki, M.; Vaferi, B.; Rahimpour, M. R. Comparison the capability of artificial neural network (ANN) and EOS for prediction of solid solubilities in supercritical carbon dioxide Fluid Phase Equilib. 2011, 308 (1-2) 35-43
81. Chouai, A.; Laugier, S.; Richon, D. Modeling of thermodynamic properties using neural networks: Application to refrigerants Fluid Phase Equilib. 2002, 199 (1-2) 53-62
82. Safamirzaei, M.; Modarress, H.; Mohsen-Nia, M. Modeling and predicting the Henry's law constants of methyl ketones in aqueous sodium sulfate solutions with artificial neural network Fluid Phase Equilib. 2008, 266 (1-2) 187-194
83. Safamirzaei, M.; Modarress, H. Modeling and predicting solubility of n-alkanes in water Fluid Phase Equilib. 2011, 309 (1) 53-61
84. Safamirzaei, M.; Modarress, H.; Mohsen-Nia, M. Modeling the hydrogen solubility in methanol, ethanol, 1-propanol and 1-butanol Fluid Phase Equilib. 2010, 289 (1) 32-39
85. http://www.mathworks.com.
86. Rostamizadeh, M.; Rezakazemi, M.; Shahidi, K.; Mohammadi, T. Gas permeation through H2-selective mixed matrix membranes: Experimental and neural network modeling Int. J. Hydrogen Energy 2013, 38 (2) 1128-1135
87. Mirkhani, S. A.; Gharagheizi, F.; Sattari, M. A QSPR model for prediction of diffusion coefficient of non-electrolyte organic compounds in air at ambient condition Chemosphere 2012, 86 (9) 959-966
88. Consonni, V.; Ballabio, D.; Todeschini, R. Comments on the Definition of the Q2 Parameter for QSAR Validation J. Chem. Inf. Model. 2009, 49 (7) 1669-1678
89. Gramatica, P. Principles of QSAR models validation: internal and external QSAR Comb. Sci. 2007, 26 (5) 694-701
90. Golbraikh, A.; Tropsha, A. Beware of q2! J. Mol. Graphics Modell. 2002, 20 (4) 269-276
91. Pratim Roy, P.; Paul, S.; Mitra, I.; Roy, K. On Two Novel Parameters for Validation of Predictive QSAR Models Molecules 2009, 14 (5) 1660-1701
92. Shi, L. M.; Fang, H.; Tong, W.; Wu, J.; Perkins, R.; Blair, R. M.; Branham, W. S.; Dial, S. L.; Moland, C. L.; Sheehan, D. M. QSAR Models Using a Large Diverse Set of Estrogens J. Chem. Inf. Comput. Sci. 2000, 41 (1) 186-195
93. Schüürmann, G.; Ebert, R.-U.; Chen, J.; Wang, B.; Kühne, R. External Validation and Prediction Employing the Predictive Squared Correlation Coefficient · Test Set Activity Mean vs Training Set Activity Mean J. Chem. Inf. Model. 2008, 48 (11) 2140-2145
94. Consonni, V.; Ballabio, D.; Todeschini, R. Evaluation of model predictive ability by external validation techniques J. Chemom. 2010, 24 (3-4) 194-201