{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T19:17:48Z","timestamp":1774034268408,"version":"3.50.1"},"reference-count":69,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,3,30]],"date-time":"2018-03-30T00:00:00Z","timestamp":1522368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Higher Education (MOHE) Malaysia","award":["FRGS14-102-0343"],"award-info":[{"award-number":["FRGS14-102-0343"]}]},{"name":"Portuguese National Funding Agency for science, research and technology (FCT)","award":["UID\/CEC\/00319\/2013"],"award-info":[{"award-number":["UID\/CEC\/00319\/2013"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>The adoption of forecasting approaches such as the multiplicative Holt-Winters (MHW) model is preferred in business, especially for the prediction of future events having seasonal and other causal variations. However, in the MHW model the initial values of the time-series parameters and smoothing constants are incorporated by a recursion process to estimate and update the level (LT), growth rate (bT) and seasonal component (SNT). The current practice of integrating and\/or determining the initial value of LT is a stationary process, as it restricts the scope of adjustment with the progression of time and, thereby, the forecasting accuracy is compromised, while the periodic updating of LT is avoided, presumably due to the computational complexity. To overcome this obstacle, a fuzzy logic-based prediction model is developed to evaluate LT dynamically and to embed its value into the conventional MHW approach. The developed model is implemented in the MATLAB Fuzzy Logic Toolbox along with an optimal smoothing constant-seeking program. The new model, proposed as a collaborative approach, is tested with real-life data gathered from a local manufacturer and also for two industrial cases extracted from literature. In all cases, a significant improvement in forecasting accuracy is achieved.<\/jats:p>","DOI":"10.3390\/app8040530","type":"journal-article","created":{"date-parts":[[2018,3,30]],"date-time":"2018-03-30T12:43:48Z","timestamp":1522413828000},"page":"530","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A Collaborative Multiplicative Holt-Winters Forecasting Approach with Dynamic Fuzzy-Level Component"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4929-695X","authenticated-orcid":false,"given":"H.","family":"Kays","sequence":"first","affiliation":[{"name":"Department of Manufacturing and Materials Engineering, International Islamic University Malaysia, Jalan Gombak, 53100 Kuala Lumpur, Malaysia"}]},{"given":"A.","family":"Karim","sequence":"additional","affiliation":[{"name":"Faculty of Science and Engineering, Queensland University of Technology, 2 George St, Brisbane 4000, Australia"}]},{"given":"Mohd","family":"Daud","sequence":"additional","affiliation":[{"name":"Department of Manufacturing and Materials Engineering, International Islamic University Malaysia, Jalan Gombak, 53100 Kuala Lumpur, Malaysia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2299-1859","authenticated-orcid":false,"given":"Maria","family":"Varela","sequence":"additional","affiliation":[{"name":"Department of Production and Systems, School of Engineering, University of Minho, 4800-058 Guimar\u00e3es, Portugal"}]},{"given":"Goran","family":"Putnik","sequence":"additional","affiliation":[{"name":"Department of Production and Systems, School of Engineering, University of Minho, 4800-058 Guimar\u00e3es, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4917-2474","authenticated-orcid":false,"given":"Jos\u00e9","family":"Machado","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, School of Engineering, University of Minho, 4800-058 Guimar\u00e3es, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"213","DOI":"10.5539\/ijbm.v5n7p213","article-title":"Customer Brand Loyalty","volume":"5","author":"Mao","year":"2010","journal-title":"Int. J. Bus. Manag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1016\/j.ijforecast.2009.11.001","article-title":"Bayesian forecasting of parts demand","volume":"26","author":"Yelland","year":"2010","journal-title":"Int. J. Forecast."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1080\/09537280903454149","article-title":"Structuring and integrating human knowledge in demand forecasting: A judgemental adjustment approach","volume":"21","author":"Marmier","year":"2010","journal-title":"Prod. Plan. Control"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1016\/j.cie.2007.06.005","article-title":"Forecasting Thailand\u2019s rice export: Statistical techniques vs. artificial neural networks","volume":"53","author":"Co","year":"2007","journal-title":"Comput. Ind. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1287\/mnsc.6.3.324","article-title":"Forecasting sales by exponentially weighted moving averages","volume":"6","author":"Winters","year":"1960","journal-title":"Manag. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1086\/208516","article-title":"Mood states and consumer behavior: A critical review","volume":"12","author":"Gardner","year":"1985","journal-title":"J. Consum. Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1287\/mnsc.36.4.490","article-title":"Evaluating forecast performance in an inventory control system","volume":"36","author":"Gardner","year":"1990","journal-title":"Manag. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1057\/palgrave.jors.2601589","article-title":"Short-term electricity demand forecasting using double seasonal exponential smoothing","volume":"54","author":"Taylor","year":"2003","journal-title":"J. Oper. Res. Soc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.ijforecast.2005.08.002","article-title":"Exponential smoothing model selection for forecasting","volume":"22","author":"Billah","year":"2006","journal-title":"Int. J. Forecast."},{"key":"ref_10","unstructured":"Brown, R.G. (1959). Statistical Forecasting for Inventory Control, McGraw\/Hill."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.ijforecast.2003.09.015","article-title":"Forecasting seasonals and trends by exponentially weighted moving averages","volume":"20","author":"Holt","year":"2004","journal-title":"Int. J. Forecast."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1016\/S0169-2070(01)00110-8","article-title":"A state space framework for automatic forecasting using exponential smoothing methods","volume":"18","author":"Hyndman","year":"2002","journal-title":"Int. J. Forecast."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/S0169-2070(98)00040-5","article-title":"How should additive Holt-Winters estimates be corrected?","volume":"14","author":"Lawton","year":"1998","journal-title":"Int. J. Forecast."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/S0377-2217(00)00062-X","article-title":"A spreadsheet modeling approach to the Holt-Winters optimal forecasting","volume":"131","author":"Segura","year":"2001","journal-title":"Eur. J. Oper. Res."},{"key":"ref_15","unstructured":"Bruce, L., Richard, T., and Anne, B. (2005). Forecasting Time Series and Regression, Thomson Brooks\/Cole."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/S0169-2070(01)00081-4","article-title":"Forecasting models and prediction intervals for the multiplicative Holt-Winters method","volume":"17","author":"Koehler","year":"2001","journal-title":"Int. J. Forecast."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/0169-2070(91)90030-Y","article-title":"Prediction intervals for multiplicative Holt-Winters","volume":"7","author":"Chatfield","year":"1991","journal-title":"Int. J. Forecast."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Kays, H.E., Karim, A.N.M., Hasan, M., and Sarker, R.A. (2018). Impact of initial level and growth rate in multiplicative HW model on bullwhip effect in a supply chain. Data and Decision Sciences in Action, Springer.","DOI":"10.1007\/978-3-319-55914-8_26"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s11424-014-3299-y","article-title":"A self-similar local neuro-fuzzy model for short-term demand forecasting","volume":"27","author":"Hassani","year":"2014","journal-title":"J. Syst. Sci. Complex."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/ijdsst.2015010101","article-title":"Collaborative negotiation platform using a dynamic multi-criteria decision model","volume":"7","author":"Varela","year":"2015","journal-title":"Int. J. Decis. Support Syst. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lozano, \u00c1., De Paz, J.F., Villarrubia Gonz\u00e1lez, G., Iglesia, D.H., and Bajo, J. (2018). Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems. Appl. Sci., 8.","DOI":"10.3390\/app8010067"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Alfian, G., Rhee, J., Ijaz, M.F., Syafrudin, M., and Fitriyani, N.L. (2017). Performance Analysis of a Forecasting Relocation Model for One-Way Carsharing. Appl. Sci., 7.","DOI":"10.3390\/app7060598"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Lu, J., Bai, D., Zhang, N., Yu, T., and Zhang, X. (2016). Fuzzy Case-Based Reasoning System. Appl. Sci., 6.","DOI":"10.3390\/app6070189"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.csda.2006.02.010","article-title":"A decision support system methodology for forecasting of time series based on soft computing","volume":"51","author":"Segura","year":"2006","journal-title":"Comput. Stat. Data Anal."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3253","DOI":"10.1016\/j.physa.2008.01.095","article-title":"A granular time series approach to long-term forecasting and trend forecasting","volume":"387","author":"Dong","year":"2008","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3839","DOI":"10.1016\/j.eswa.2008.02.042","article-title":"Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting","volume":"36","author":"Akay","year":"2009","journal-title":"Expert Syst. Appl."},{"key":"ref_27","unstructured":"Bowerman, B.L., O\u2019Connell, R.T., and Koehler, A.B. (2005). Forecasting, Time Series, and Regression: An Applied Approach, South-Western Pub."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/j.ijforecast.2006.03.005","article-title":"Exponential smoothing: The state of the art\u2014Part II","volume":"22","author":"Gardner","year":"2006","journal-title":"Int. J. Forecast."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1016\/S0377-2217(03)00360-6","article-title":"Exponential smoothing models: Means and variances for lead-time demand","volume":"158","author":"Snyder","year":"2004","journal-title":"Eur. J. Oper. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1016\/S0169-2070(03)00003-7","article-title":"Exponential smoothing with a damped multiplicative trend","volume":"19","author":"Taylor","year":"2003","journal-title":"Int. J. Forecast."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1075","DOI":"10.1080\/02664760701592125","article-title":"Holt-Winters forecasting: An alternative formulation applied to UK air passenger data","volume":"34","author":"Segura","year":"2007","journal-title":"J. Appl. Stat."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1016\/j.ijforecast.2010.02.012","article-title":"Holt\u2019s exponential smoothing and neural network models for forecasting interval-valued time series","volume":"27","author":"Maia","year":"2011","journal-title":"Int. J. Forecast."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1080\/00405009808658668","article-title":"Fuzzy Adaptation of the Holt\u2013Winter Model for Textile Sales-forecasting","volume":"89","author":"Vroman","year":"1998","journal-title":"J. Text. Inst."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/S0169-2070(00)00053-4","article-title":"Long lead-time forecasting of UK air passengers by Holt-Winters methods with damped trend","volume":"17","author":"Grubb","year":"2001","journal-title":"Int. J. Forecast."},{"key":"ref_35","first-page":"421","article-title":"Forecasting Electricity Consumption by Using Holt-Winters and Seasonal Regression Models","volume":"8","year":"2016","journal-title":"Econ. Org."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.ijpe.2010.05.009","article-title":"Joint optimisation of demand forecasting and stock control parameters","volume":"127","author":"Tratar","year":"2010","journal-title":"Int. J. Prod. Econ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.ejor.2009.10.003","article-title":"Triple seasonal methods for short-term electricity demand forecasting","volume":"204","author":"Taylor","year":"2010","journal-title":"Eur. J. Oper. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3235","DOI":"10.1109\/TPWRS.2013.2252929","article-title":"Short-term forecasting of anomalous load using rule-based triple seasonal methods","volume":"28","author":"Arora","year":"2013","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1016\/j.ijepes.2014.07.043","article-title":"Short term load forecasting using wavelet transform combined with Holt-Winters and weighted nearest neighbor models","volume":"64","author":"Sudheer","year":"2015","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/j.eswa.2015.08.052","article-title":"Smoothing inventory decision rules in seasonal supply chains","volume":"44","author":"Costantino","year":"2016","journal-title":"Expert Syst. Appl."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1016\/j.cie.2011.07.002","article-title":"A collaborative demand forecasting process with event-based fuzzy judgements","volume":"61","author":"Cheikhrouhou","year":"2011","journal-title":"Comput. Ind. Eng."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"402","DOI":"10.4028\/www.scientific.net\/AMR.903.402","article-title":"Forecasting demand: Development of a fuzzy growth adjusted Holt-Winters approach","volume":"Volume 903","author":"Abdesselam","year":"2014","journal-title":"Advanced Materials Research"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2265","DOI":"10.1016\/j.eswa.2009.07.046","article-title":"Application of fuzzy inference system and nonlinear regression models for predicting rock brittleness","volume":"37","author":"Yagiz","year":"2010","journal-title":"Expert Syst. Appl."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"7558","DOI":"10.1016\/j.eswa.2010.12.111","article-title":"Approach to prediction of laser cutting quality by employing fuzzy expert system","volume":"38","author":"Syn","year":"2011","journal-title":"Expert Syst. Appl."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.atmosres.2011.02.015","article-title":"Rainfall events prediction using rule-based fuzzy inference system","volume":"101","author":"Asklany","year":"2011","journal-title":"Atmos. Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00773-013-0226-1","article-title":"Prediction of wave parameters by using fuzzy inference system and the parametric models along the south coasts of the Black Sea","volume":"19","year":"2014","journal-title":"J. Mar. Sci. Technol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"10819","DOI":"10.1007\/s12517-015-1952-y","article-title":"Application of fuzzy inference system for prediction of rock fragmentation induced by blasting","volume":"8","author":"Shams","year":"2015","journal-title":"Arab. J. Geosci."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"3145","DOI":"10.1109\/TCYB.2015.2498522","article-title":"A switched system approach to exponential stabilization of sampled-data T\u2013S fuzzy systems with packet dropouts","volume":"46","author":"Wag","year":"2016","journal-title":"IEEE Trans. Cybern."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1016\/j.ymssp.2015.09.017","article-title":"Robust H\u221e output-feedback control for path following of autonomous ground vehicles","volume":"70","author":"Hu","year":"2016","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.neucom.2014.01.025","article-title":"Fuzzy model-based predictive control of dissolved oxygen in activated sludge processes","volume":"136","author":"Yang","year":"2014","journal-title":"Neurocomputing"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2524","DOI":"10.1016\/j.jfranklin.2016.09.020","article-title":"Actuator and sensor faults estimation based on proportional integral observer for TS fuzzy model","volume":"354","author":"Youssef","year":"2017","journal-title":"J. Franklin Inst."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1109\/TFUZZ.2016.2593921","article-title":"Fuzzy fault detection filter design for t\u2013s fuzzy systems in the finite-frequency domain","volume":"25","author":"Chibani","year":"2017","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1016\/j.enpol.2008.10.051","article-title":"A fuzzy inference model for short-term load forecasting","volume":"37","author":"Mamlook","year":"2009","journal-title":"Energy Policy"},{"key":"ref_54","first-page":"297","article-title":"An Intelligence-Based Fuzzy Inference System for Smart Home Real-Time Load Forecasting","volume":"50","author":"Huang","year":"2012","journal-title":"Procedia Eng."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1623\/hysj.54.2.261","article-title":"Comparison of fuzzy inference systems for streamflow prediction","volume":"54","year":"2009","journal-title":"Hydrol. Sci. J."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.conbuildmat.2015.08.096","article-title":"Adaptive neuro fuzzy prediction of deflection and cracking behavior of NSM strengthened RC beams","volume":"98","author":"Darain","year":"2015","journal-title":"Constr. Build. Mater."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1080\/10426914.2015.1037901","article-title":"A fuzzy logic-based prediction model for kerf width in laser beam machining","volume":"31","author":"Hossain","year":"2016","journal-title":"Mater. Manuf. Process."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1061\/(ASCE)WR.1943-5452.0000248","article-title":"Bilevel optimization of regional water resources allocation problem under fuzzy random environment","volume":"139","author":"Xu","year":"2012","journal-title":"J. Water Resour. Plan. Manag."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"15425","DOI":"10.1016\/j.eswa.2011.06.019","article-title":"Fuzzy forecasting based on high-order fuzzy logical relationships and automatic clustering techniques","volume":"38","author":"Chen","year":"2011","journal-title":"Expert Syst. Appl."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.jhydrol.2011.01.013","article-title":"Generation of ensemble precipitation forecast from single-valued quantitative precipitation forecast for hydrologic ensemble prediction","volume":"399","author":"Wu","year":"2011","journal-title":"J. Hydrol."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"10594","DOI":"10.1016\/j.eswa.2011.02.098","article-title":"Multivariate fuzzy forecasting based on fuzzy time series and automatic clustering techniques","volume":"38","author":"Chen","year":"2011","journal-title":"Expert Syst. Appl."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1109\/JSTARS.2013.2283402","article-title":"Proof of concept of an altimeter-based river forecasting system for transboundary flow inside Bangladesh","volume":"7","author":"Hossain","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1002\/met.1467","article-title":"Validation of remote-sensing precipitation products for Angola","volume":"22","author":"Pombo","year":"2015","journal-title":"Meteorol. Appl."},{"key":"ref_64","unstructured":"Li, H., and Yen, V.C. (1995). Fuzzy Sets and Fuzzy Decision-Making, CRC Press."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Abele, E., Anderl, R., and Birkhofer, H. (2005). Environmentally-Friendly Product Development, Springer.","DOI":"10.1007\/b138604"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0167-8809(00)00272-3","article-title":"Assessment of the contribution of sustainability indicators to sustainable development: A novel approach using fuzzy set theory","volume":"86","author":"Cornelissen","year":"2001","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/S0898-1221(01)00277-2","article-title":"Ranking fuzzy numbers with an area between the centroid point and original point","volume":"43","author":"Chu","year":"2002","journal-title":"Comput. Math. Appl."},{"key":"ref_68","first-page":"836","article-title":"Adaptive resource allocation in OFDM systems using GA and fuzzy rule base system","volume":"18","author":"Rahman","year":"2012","journal-title":"World Appl. Sci. J."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1016\/j.ast.2010.12.003","article-title":"Prediction of aerodynamic characteristics of an aircraft model with and without winglet using fuzzy logic technique","volume":"15","author":"Hossain","year":"2011","journal-title":"Aerosp. Sci. Technol."}],"container-title":["Applied Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-3417\/8\/4\/530\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:59:07Z","timestamp":1760194747000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-3417\/8\/4\/530"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3,30]]},"references-count":69,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,4]]}},"alternative-id":["app8040530"],"URL":"https:\/\/doi.org\/10.3390\/app8040530","relation":{},"ISSN":["2076-3417"],"issn-type":[{"value":"2076-3417","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,3,30]]}}}