UPSI Digital Repository (UDRep)
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UPSI Digital Repository (UDRep)
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| Abstract : Universiti Pendidikan Sultan Idris |
| The problem complexity of multi-criteria decision-making (MCDM) has been raised in the distribution of coronavirus disease 2019 (COVID-19) vaccines, which required solid and robust MCDM methods. Compared with other MCDM methods, the fuzzy-weighted zero-inconsistency (FWZIC) method and fuzzy decision by opinion score method (FDOSM) have demonstrated their solidity in solving different MCDM challenges. However, the fuzzy sets used in these methods have neglected the refusal concept and limited the restrictions on their constants. To end this, considering the advantage of the T-spherical fuzzy sets (T-SFSs) in handling the uncertainty in the data and obtaining information with more degree of freedom, this study has extended FWZIC and FDOSM methods into the T-SFSs environment (called T-SFWZIC and T-SFDOSM) to be used in the distribution of COVID-19 vaccines. The methodology was formulated on the basis of decision matrix adoption and development phases. The first phase described the adopted decision matrix used in the COVID-19 vaccine distribution. The second phase presented the sequential formulation steps of T-SFWZIC used for weighting the distribution criteria followed by T-SFDOSM utilised for prioritising the vaccine recipients. Results revealed the following: (1) T-SFWZIC effectively weighted the vaccine distribution criteria based on several parameters including T = 2, T = 4, T = 6, T = 8, and T = 10. Amongst all parameters, the age criterion received the highest weight, whereas the geographic locations severity criterion has the lowest weight. (2) According to the T parameters, a considerable variance has occurred on the vaccine recipient orders, indicating that the existence of T values affected the vaccine distribution. (3) In the individual context of T-SFDOSM, no unique prioritisation was observed based on the obtained opinions of each expert. (4) The group context of T-SFDOSM used in the prioritisation of vaccine recipients was considered the final distribution result as it unified the differences found in an individual context. The evaluation was performed based on systematic ranking assessment and sensitivity analysis. This evaluation showed that the prioritisation results based on each T parameter were subject to a systematic ranking that is supported by high correlation results over all discussed scenarios of changing criteria weights values. |
| References |
Abdulkareem, K. H. (2020). A novel multi-perspective benchmarking framework for selecting image dehazing intelligent algorithms based on BWM and group VIKOR techniques. International Journal of Information Technology & Decision Making, 93, 1-49. Retrieved from www.scopus.com Abdullateef, B. N., Elias, N. F., Mohamed, H., Zaidan, A. A., & Zaidan, B. B. (2016). An evaluation and selection problems of OSS-LMS packages. SpringerPlus, 5(1), 1-35. doi:10.1186/s40064-016-1828-y Alaa, M., Albakri, I. S. M. A., Singh, C. K. S., Hammed, H., Zaidan, A. A., Zaidan, B. B., . . . Jasim, A. N. (2019). Assessment and ranking framework for the english skills of pre-service teachers based on fuzzy delphi and TOPSIS methods. IEEE Access, 7, 126201-126223. doi:10.1109/ACCESS.2019.2936898 Alamoodi, A. H., Garfan, S., Zaidan, B. B., Zaidan, A. A., Shuwandy, M. L., Alaa, M., . . . Alobaidi, O. R. (2020). A systematic review into the assessment of medical apps: Motivations, challenges, recommendations and methodological aspect. Health and Technology, 10(5), 1045-1061. doi:10.1007/s12553-020-00451-4 Alamoodi, A. H., Zaidan, B. B., Zaidan, A. A., Albahri, O. S., Chen, J., Chyad, M. A., . . . Aleesa, A. M. (2021). Machine learning-based imputation soft computing approach for large missing scale and non-reference data imputation. Chaos, Solitons and Fractals, 151 doi:10.1016/j.chaos.2021.111236 Alamoodi, A. H., Zaidan, B. B., Zaidan, A. A., Albahri, O. S., Mohammed, K. I., Malik, R. Q., . . . Alaa, M. (2021). Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: A systematic review. Expert Systems with Applications, 167 doi:10.1016/j.eswa.2020.114155 Albahri, A. S., Albahri, O. S., Zaidan, A. A., Alnoor, A., Alsattar, H. A., Mohammed, R., . . . Ahmed, M. A. (2022). Integration of fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score methods under a q-rung orthopair environment: A distribution case study of COVID-19 vaccine doses. Computer Standards and Interfaces, 80 doi:10.1016/j.csi.2021.103572 Albahri, A. S., Albahri, O. S., Zaidan, A. A., Zaidan, B. B., Hashim, M., Alsalem, M. A., . . . Baqer, M. J. (2019). Based multiple heterogeneous wearable sensors: A smart real-time health monitoring structured for hospitals distributor. IEEE Access, 7, 37269-37323. doi:10.1109/ACCESS.2019.2898214 Albahri, A. S., Al-Obaidi, J. R., Zaidan, A. A., Albahri, O. S., Hamid, R. A., Zaidan, B. B., . . . Hashim, M. (2020). Multi-biological laboratory examination framework for the prioritization of patients with COVID-19 based on integrated AHP and group VIKOR methods. International Journal of Information Technology and Decision Making, 19(5), 1247-1269. doi:10.1142/S0219622020500285 Albahri, A. S., Alwan, J. K., Taha, Z. K., Ismail, S. F., Hamid, R. A., Zaidan, A. A., . . . Alsalem, M. A. (2021). IoT-based telemedicine for disease prevention and health promotion: State-of-the-art. Journal of Network and Computer Applications, 173 doi:10.1016/j.jnca.2020.102873 Albahri, A. S., Hamid, R. A., Albahri, O. S., & Zaidan, A. A. (2021). Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy–TOPSIS methods. Artificial Intelligence in Medicine, 111 doi:10.1016/j.artmed.2020.101983 Albahri, A. S., Hamid, R. A., Albahri, O. S., & Zaidan, A. A. (2021). Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy–TOPSIS methods. Artificial Intelligence in Medicine, 111 doi:10.1016/j.artmed.2020.101983 Albahri, A. S., Hamid, R. A., Alwan, J., Al-qays, Z. T., Zaidan, A. A., Zaidan, B. B., . . . Madhloom, H. T. (2020). Role of biological data mining and machine learning techniques in detecting and diagnosing the novel coronavirus (COVID-19): A systematic review. Journal of Medical Systems, 44(7) doi:10.1007/s10916-020-01582-x Albahri, A. S., Zaidan, A. A., Albahri, O. S., Zaidan, B. B., Alamoodi, A. H., Shareef, A. H., . . . Mohammed, K. I. (2021). Development of IoT-based mhealth framework for various cases of heart disease patients. Health and Technology, 11(5), 1013-1033. doi:10.1007/s12553-021-00579-x Albahri, A. S., Zaidan, A. A., Albahri, O. S., Zaidan, B. B., & Alsalem, M. A. (2018). Real-time fault-tolerant mHealth system: Comprehensive review of healthcare services, opens issues, challenges and methodological aspects. Journal of Medical Systems, 42(8) doi:10.1007/s10916-018-0983-9 Albahri, O. (2021). New mHealth hospital selection framework supporting decentralised telemedicine architecture for outpatient cardiovascular disease-based integrated techniques: Haversine-GPS and AHP-VIKOR. Journal of Ambient Intelligence and Humanized Computing, , 1-21. Retrieved from www.scopus.com Albahri, O. S., Albahri, A. S., Mohammed, K. I., Zaidan, A. A., Zaidan, B. B., Hashim, M., & Salman, O. H. (2018). Systematic review of real-time remote health monitoring system in triage and priority-based sensor technology: Taxonomy, open challenges, motivation and recommendations. Journal of Medical Systems, 42(5) doi:10.1007/s10916-018-0943-4 Albahri, O. S., Albahri, A. S., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., Mohsin, A. H., . . . Shareef, A. H. (2019). Fault-tolerant mHealth framework in the context of IoT-based real-time wearable health data sensors. IEEE Access, 7, 50052-50080. doi:10.1109/ACCESS.2019.2910411 Albahri, O. S., Al-Obaidi, J. R., Zaidan, A. A., Albahri, A. S., Zaidan, B. B., Salih, M. M., . . . Zulkifli, C. Z. (2020). Helping doctors hasten COVID-19 treatment: Towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods. Computer Methods and Programs in Biomedicine, 196 doi:10.1016/j.cmpb.2020.105617 Albahri, O. S., Zaidan, A. A., Albahri, A. S., Alsattar, H. A., Mohammed, R., Aickelin, U., . . . Al-Obaidi, J. R. (2022). Novel dynamic fuzzy decision-making framework for COVID-19 vaccine dose recipients. Journal of Advanced Research, 37, 147-168. doi:10.1016/j.jare.2021.08.009 Albahri, O. S., Zaidan, A. A., Albahri, A. S., Zaidan, B. B., Abdulkareem, K. H., Al-qaysi, Z. T., . . . Rashid, N. A. (2020). Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects. Journal of Infection and Public Health, 13(10), 1381-1396. doi:10.1016/j.jiph.2020.06.028 Albahri, O. S., Zaidan, A. A., Salih, M. M., Zaidan, B. B., Khatari, M. A., Ahmed, M. A., . . . Alazab, M. (2021). Multidimensional benchmarking of the active queue management methods of network congestion control based on extension of fuzzy decision by opinion score method. International Journal of Intelligent Systems, 36(2), 796-831. doi:10.1002/int.22322 Albahri, O. S., Zaidan, A. A., Zaidan, B. B., Hashim, M., Albahri, A. S., & Alsalem, M. A. (2018). Real-time remote health-monitoring systems in a medical centre: A review of the provision of healthcare services-based body sensor information, open challenges and methodological aspects. Journal of Medical Systems, 42(9) doi:10.1007/s10916-018-1006-6 Almahdi, E. M., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., Albahri, O. S., & Albahri, A. S. (2019). Mobile patient monitoring systems from a benchmarking aspect: Challenges, open issues and recommended solutions. Journal of Medical Systems, 43(7) doi:10.1007/s10916-019-1336-z Almahdi, E. M., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., Albahri, O. S., & Albahri, A. S. (2019). Mobile-based patient monitoring systems: A prioritisation framework using multi-criteria decision-making techniques. Journal of Medical Systems, 43(7) doi:10.1007/s10916-019-1339-9 Almahdi, E. M., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., Albahri, O. S., & Albahri, A. S. (2019). Mobile-based patient monitoring systems: A prioritisation framework using multi-criteria decision-making techniques. Journal of Medical Systems, 43(7) doi:10.1007/s10916-019-1339-9 Alsalem, M. A., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alamoodi, A. H., Albahri, A. S., . . . Mohammed, K. I. (2019). Multiclass benchmarking framework for automated acute leukaemia detection and classification based on BWM and group-VIKOR. Journal of Medical Systems, 43(7) doi:10.1007/s10916-019-1338-x Alsalem, M. A., Zaidan, A. A., Zaidan, B. B., Hashim, M., Albahri, O. S., Albahri, A. S., . . . Mohammed, K. I. (2018). Systematic review of an automated multiclass detection and classification system for acute leukaemia in terms of evaluation and benchmarking, open challenges, issues and methodological aspects. Journal of Medical Systems, 42(11) doi:10.1007/s10916-018-1064-9 Bubar, K. M., Reinholt, K., Kissler, S. M., Lipsitch, M., Cobey, S., Grad, Y. H., & Larremore, D. B. (2020). Model-informed COVID-19 vaccine prioritization strategies by age and serostatus. MedRxiv, Retrieved from www.scopus.com Chen, T., Wang, Y. -., & Wu, H. -. (2021). Analyzing the impact of vaccine availability on alternative supplier selection amid the covid-19 pandemic: A cfgm-ftopsis-fwi approach. Healthcare (Switzerland), 9(1) doi:10.3390/healthcare9010071 Dawood, K. A. (2020). Novel multi-perspective usability evaluation framework for selection of open source software based on BWM and group VIKOR techniques. International Journal of Information Technology & Decision Making, Retrieved from www.scopus.com Dizbay, İ. E., & Öztürkoğlu, Ö. (2021). Determining significant factors affecting vaccine demand and factor relationships using fuzzy DEMATEL method doi:10.1007/978-3-030-51156-2_79 Retrieved from www.scopus.com Dooling, K. (2020). COVID-19 vaccine prioritization: Work group considerations. COVID-19 Vaccine Prioritization: Work Group Considerations, Retrieved from www.scopus.com Enaizan, O., Zaidan, A. A., Alwi, N. H. M., Zaidan, B. B., Alsalem, M. A., Albahri, O. S., & Albahri, A. S. (2020). Electronic medical record systems: Decision support examination framework for individual, security and privacy concerns using multi-perspective analysis. Health and Technology, 10(3), 795-822. doi:10.1007/s12553-018-0278-7 Garg, H., Munir, M., Ullah, K., Mahmood, T., & Jan, N. (2018). Algorithm for T-spherical fuzzy multi-attribute decision making based on improved interactive aggregation operators. Symmetry, 10(12) doi:10.3390/sym10120670 Guleria, A., & Bajaj, R. K. (2021). T-spherical fuzzy soft sets and its aggregation operators with application in decision-making. Scientia Iranica, 28(2 E), 1014-1029. doi:10.24200/sci.2019.53027.3018 Hamid, R. A., Albahri, A., Albahri, O., & Zaidan, A. (2021). Dempster–Shafer theory for classification and hybridised models of multi-criteria decision analysis for prioritisation: A telemedicine framework for patients with heart diseases. J Ambient Intell Human Comput, , 1-35. Retrieved from www.scopus.com Hezam, I. M., Nayeem, M. K., Foul, A., & Alrasheedi, A. F. (2021). COVID-19 vaccine: A neutrosophic MCDM approach for determining the priority groups. Results in Physics, 20 doi:10.1016/j.rinp.2020.103654 Ibrahim, N. K., Hammed, H., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., . . . Alaa, M. (2019). Multi-criteria evaluation and benchmarking for young learners' english language mobile applications in terms of LSRW skills. IEEE Access, 7, 146620-146651. doi:10.1109/ACCESS.2019.2941640 Jumaah, F. M., Zadain, A. A., Zaidan, B. B., Hamzah, A. K., & Bahbibi, R. (2018). Decision-making solution based multi-measurement design parameter for optimization of GPS receiver tracking channels in static and dynamic real-time positioning multipath environment. Measurement: Journal of the International Measurement Confederation, 118, 83-95. doi:10.1016/j.measurement.2018.01.011 Jumaah, F. M., Zaidan, A. A., Zaidan, B. B., Bahbibi, R., Qahtan, M. Y., & Sali, A. (2018). Technique for order performance by similarity to ideal solution for solving complex situations in multi-criteria optimization of the tracking channels of GPS baseband telecommunication receivers. Telecommunication Systems, 68(3), 425-443. doi:10.1007/s11235-017-0401-5 Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., & Muzammil, H. (2018). Based real time remote health monitoring systems: A review on patients prioritization and related "big data" using body sensors information and communication technology. Journal of Medical Systems, 42(2) doi:10.1007/s10916-017-0883-4 Khatari, M., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., & Alsalem, M. A. (2019). Multi-criteria evaluation and benchmarking for active queue management methods: Open issues, challenges and recommended pathway solutions. International Journal of Information Technology and Decision Making, 18(4), 1187-1242. doi:10.1142/S0219622019300039 Liburd, L. C., Hall, J. E., Mpofu, J. J., Williams, S. M., Bouye, K., & Penman-Aguilar, A. (2019). Addressing health equity in public health practice: Frameworks, promising strategies, and measurement considerations doi:10.1146/annurev-publhealth-040119-094119 Retrieved from www.scopus.com Liu, P., Zhu, B., & Wang, P. (2019). A multi-attribute decision-making approach based on spherical fuzzy sets for yunnan Baiyao’s R&D project selection problem. International Journal of Fuzzy Systems, 21(7), 2168-2191. doi:10.1007/s40815-019-00687-x Mahmood, T., Ullah, K., Khan, Q., & Jan, N. (2019). An approach toward decision-making and medical diagnosis problems using the concept of spherical fuzzy sets. Neural Computing and Applications, 31(11), 7041-7053. doi:10.1007/s00521-018-3521-2 Malik, R. (2021). Novel roadside unit positioning framework in the context of the vehicle-to-infrastructure communication system based on AHP—Entropy for weighting and borda—VIKOR for uniform ranking. Int J Inform Technol Decision Making, , 1-34. Retrieved from www.scopus.com Mohammed, K. I., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., Albahri, A. S., . . . Hashim, M. (2019). Real-time remote-health monitoring systems: A review on patients prioritisation for multiple-chronic diseases, taxonomy analysis, concerns and solution procedure. Journal of Medical Systems, 43(7) doi:10.1007/s10916-019-1362-x Mohammed, T. J., Albahri, A. S., Zaidan, A. A., Albahri, O. S., Al-Obaidi, J. R., Zaidan, B. B., . . . Hadi, S. M. (2021). Convalescent-plasma-transfusion intelligent framework for rescuing COVID-19 patients across centralised/decentralised telemedicine hospitals based on AHP-group TOPSIS and matching component. Applied Intelligence, 51(5), 2956-2987. doi:10.1007/s10489-020-02169-2 Mohsin, A. H., Zaidan, A. A., Zaidan, B. B., Mohammed, K. I., Albahri, O. S., Albahri, A. S., & Alsalem, M. A. (2021). PSO–Blockchain-based image steganography: Towards a new method to secure updating and sharing COVID-19 data in decentralised hospitals intelligence architecture. Multimedia Tools and Applications, 80(9), 14137-14161. doi:10.1007/s11042-020-10284-y Munguía-López, A. C., & Ponce-Ortega, J. M. (2021). Fair allocation of potential COVID-19 vaccines using an optimization-based strategy. Process Integration and Optimization for Sustainability, 5(1), 3-12. doi:10.1007/s41660-020-00141-8 Munir, M., Kalsoom, H., Ullah, K., Mahmood, T., & Chu, Y. -. (2020). T-spherical fuzzy einstein hybrid aggregation operators and their applications in multi-attribute decision making problems. Symmetry, 12(3) doi:10.3390/sym12030365 Munir, M., Mahmood, T., & Hussain, A. (2021). Algorithm for T-spherical fuzzy MADM based on associated immediate probability interactive geometric aggregation operators. Artificial Intelligence Review, 54(8), 6033-6061. doi:10.1007/s10462-021-09959-1 Napi, N. M., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., & Albahri, A. S. (2019). Medical emergency triage and patient prioritisation in a telemedicine environment: A systematic review. Health and Technology, 9(5), 679-700. doi:10.1007/s12553-019-00357-w Qader, M. A., Zaidan, B. B., Zaidan, A. A., Ali, S. K., Kamaluddin, M. A., & Radzi, W. B. (2017). A methodology for football players selection problem based on multi-measurements criteria analysis. Measurement: Journal of the International Measurement Confederation, 111, 38-50. doi:10.1016/j.measurement.2017.07.024 Quek, S. G., Selvachandran, G., Munir, M., Mahmood, T., Ullah, K., Son, L. H., . . . Priyadarshini, I. (2019). Multi-attribute multi-perception decision-making based on generalized T-spherical fuzzy weighted aggregation operators on neutrosophic sets. Mathematics, 7(9) doi:10.3390/math7090780 Salih, M. M., Albahri, O. S., Zaidan, A. A., Zaidan, B. B., Jumaah, F. M., & Albahri, A. S. (2021). Benchmarking of AQM methods of network congestion control based on extension of interval type-2 trapezoidal fuzzy decision by opinion score method. Telecommunication Systems, 77(3), 493-522. doi:10.1007/s11235-021-00773-2 Salih, M. M., Zaidan, B. B., Zaidan, A. A., & Ahmed, M. A. (2019). Survey on fuzzy TOPSIS state-of-the-art between 2007 and 2017. Computers and Operations Research, 104, 207-227. doi:10.1016/j.cor.2018.12.019 Salman, O. H., Zaidan, A. A., Zaidan, B. B., Naserkalid, & Hashim, M. (2017). Novel methodology for triage and prioritizing using "big data" patients with chronic heart diseases through telemedicine environmental. International Journal of Information Technology and Decision Making, 16(5), 1211-1245. doi:10.1142/S0219622017500225 Talal, M., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., Albahri, A. S., . . . Alaa, M. (2019). Comprehensive review and analysis of anti-malware apps for smartphones. Telecommunication Systems, 72(2), 285-337. doi:10.1007/s11235-019-00575-7 Tariq, I., AlSattar, H. A., Zaidan, A. A., Zaidan, B. B., Abu Bakar, M. R., Mohammed, R. T., . . . Albahri, A. S. (2020). MOGSABAT: A metaheuristic hybrid algorithm for solving multi-objective optimisation problems. Neural Computing and Applications, 32(8), 3101-3115. doi:10.1007/s00521-018-3808-3 Ullah, K., Garg, H., Mahmood, T., Jan, N., & Ali, Z. (2020). Correlation coefficients for T-spherical fuzzy sets and their applications in clustering and multi-attribute decision making. Soft Computing, 24(3), 1647-1659. doi:10.1007/s00500-019-03993-6 Ullah, K., Hassan, N., Mahmood, T., Jan, N., & Hassan, M. (2019). Evaluation of investment policy based on multi-attribute decision-making using interval valued T-spherical fuzzy aggregation operators. Symmetry, 11(3) doi:10.3390/sym11030357 Ullah, K., Mahmood, T., & Garg, H. (2020). Evaluation of the performance of search and rescue robots using T-spherical fuzzy hamacher aggregation operators. International Journal of Fuzzy Systems, 22(2), 570-582. doi:10.1007/s40815-020-00803-2 Williamson, E. J., Walker, A. J., Bhaskaran, K., Bacon, S., Bates, C., Morton, C. E., . . . Goldacre, B. (2020). Factors associated with COVID-19-related death using OpenSAFELY. Nature, 584(7821), 430-436. doi:10.1038/s41586-020-2521-4 Wu, M. -., Chen, T. -., & Fan, J. -. (2020). Divergence measure of t-spherical fuzzy sets and its applications in pattern recognition. IEEE Access, 8, 10208-10221. doi:10.1109/ACCESS.2019.2963260 Yas, Q. M., Zadain, A. A., Zaidan, B. B., Lakulu, M. B., & Rahmatullah, B. (2017). Towards on develop a framework for the evaluation and benchmarking of skin detectors based on artificial intelligent models using multi-criteria decision-making techniques. International Journal of Pattern Recognition and Artificial Intelligence, 31(3) doi:10.1142/S0218001417590029 Zaidan, A., Zaidan, B., Alsalem, M., Momani, F., & Zughoul, O. (2020). Novel multiperspective hiring framework for the selection of software programmer applicants based on AHP and group TOPSIS techniques. Int J Inf Technol Decis Mak, 18(4), 1-73. Retrieved from www.scopus.com Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., Albahri, A. S., Yas, Q. M., & Hashim, M. (2018). A review on smartphone skin cancer diagnosis apps in evaluation and benchmarking: Coherent taxonomy, open issues and recommendation pathway solution. Health and Technology, 8(4), 223-238. doi:10.1007/s12553-018-0223-9 Zaidan, A. A., Zaidan, B. B., Al-Haiqi, A., Kiah, M. L. M., Hussain, M., & Abdulnabi, M. (2015). Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS. Journal of Biomedical Informatics, 53, 390-404. doi:10.1016/j.jbi.2014.11.012 Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., Albahri, O. S., Albahri, A. S., & Qahtan, M. Y. (2020). Multi-agent learning neural network and bayesian model for real-time IoT skin detectors: A new evaluation and benchmarking methodology. Neural Computing and Applications, 32(12), 8315-8366. doi:10.1007/s00521-019-04325-3 Zaidan, A. A., Zaidan, B. B., Hussain, M., Al-Haiqi, A. M., Mat Kiah, M. L., & Abdulnabi, M. (2015). Multi-criteria analysis for OS-EMR software selection problem: A comparative study. Decision Support Systems, 78, 15-27. doi:10.1016/j.dss.2015.07.002 Zaidan, B. B., & Zaidan, A. A. (2018). Comparative study on the evaluation and benchmarking information hiding approaches based multi-measurement analysis using TOPSIS method with different normalisation, separation and context techniques. Measurement: Journal of the International Measurement Confederation, 117, 277-294. doi:10.1016/j.measurement.2017.12.019 Zaidan, B. B., & Zaidan, A. A. (2017). Software and hardware FPGA-based digital watermarking and steganography approaches: Toward new methodology for evaluation and benchmarking using multi-criteria decision-making techniques. Journal of Circuits, Systems and Computers, 26(7) doi:10.1142/S021812661750116X Zaidan, B. B., Zaidan, A. A., Abdul Karim, H., & Ahmad, N. N. (2017). A new approach based on multi-dimensional evaluation and benchmarking for data hiding techniques. International Journal of Information Technology and Decision Making, , 1-42. doi:10.1142/S0219622017500183 Zeng, S., Garg, H., Munir, M., Mahmood, T., & Hussain, A. (2019). A multi-attribute decision making process with immediate probabilistic interactive averaging aggregation operators of T-spherical fuzzy sets and its application in the selection of solar cells. Energies, 12(23) doi:10.3390/en12234436 Zeng, S., Zeng, S., Zeng, S., Munir, M., Mahmood, T., & Naeem, M. (2020). Some T-spherical fuzzy einstein interactive aggregation operators and their application to selection of photovoltaic cells. Mathematical Problems in Engineering, 2020 doi:10.1155/2020/1904362 Zughoul, O. (2020). Novel triplex procedure for ranking the ability of software engineering students based on two levels of AHP and group TOPSIS techniques. International Journal of Information Technology & Decision Making, Retrieved from www.scopus.com Zughoul, O., Momani, F., Almasri, O. H., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., . . . Hashim, M. (2018). Comprehensive insights into the criteria of student performance in various educational domains. IEEE Access, 6, 73245-73264. doi:10.1109/ACCESS.2018.2881282 |
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