Abstract
In this paper, we aimed to introduce a framework that could use the application of big data for the price management strategy in the city. A questionnaire is provided here to the public to gather the information required. This research shows that assessments, financial assistance and budget mechanisms can be based on the challenges to be explored in the questionnaire. In order to incorporate large data in this, it is essential to understand how the data can be processed and managed as well as to analyze whether the outcome obtained from these data can be used or not. To implement such a framework, we need statistical data processing, cloud computing, and optimization algorithms used during the framework development for data collection and extraction. Initial integration into the data processing subsystems includes the computational intelligence module, the transfer of data and a visual perspective on how to carry out this operation.
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References
Mani I, Bloedorn E (1997) Multi-document summarization by graph search and matching. In: Proceedings of the national conference on artificial intelligence and ninth conference on innovative applications of artificial intelligence, pp 622–628
Redavid D, Corizzo R, Malerba D (2018) An OWL ontology for supporting semantic services in big data platforms. In: 2018 IEEE international congress on big data (BigData Congress), pp 228–231
Divya K, Bhargavi P, Jyothi S (2018) Machine learning algorithms in big data analytics
Shahin FB, Tawheed P, Haque MF, Hasan MR, Khan MNR (2017) Smart home solutions with sun tracking solar panel. In: 2017 4th international conference on advances in electrical engineering (ICAEE), 2017, pp 766–769. https://doi.org/10.1109/ICAEE.2017.8255457
Haque H, Chowdhury AK, Khan MNR, Razzak MA (2021) Demand analysis of energy consumption in a residential apartment using machine learning. In: 2021 IEEE international IOT, electronics and mechatronics conference (IEMTRONICS), 2021, pp 1–6. https://doi.org/10.1109/IEMTRONICS52119.2021.9422593
Li B, Ming X, Li G (2017) Big data analytics platform for flight safety monitoring. In: 2017 IEEE 2nd international conference on big data analysis (ICBDA), pp 350–353
Alblawi AS (2017) Big data and learning analytics in higher education: demystifying variety, acquisition, storage, NLP and analytics. In: 2017 IEEE conference on big data and analytics (ICBDA), pp 124–129
Khan MNR, Iqbal MMT, Yesmin S, Mashuk AKEH, Shahin FB, Razzak MA (2018) Development of an automatic detection of pressure distortion and alarm system of endotracheal tube. In: 2018 IEEE-EMBS conference on biomedical engineering and sciences (IECBES), 2018, pp. 476–479. https://doi.org/10.1109/IECBES.2018.8626676
Ang KL-M, Ge F, Seng K (2020) Big educational data & analytics: survey, architecture and challenges. IEEE Access 8:116392–116414
Chowdhury KBQ, Hasani AMA, Labeeb K, Raihanul Karim M, Mashuk AKEH, Khan MNR (2020) IOT based garbage monitoring and clearance alert system. In: Dawn S, Balas V, Esposito A, Gope S (eds) Intelligent techniques and applications in science and technology. ICIMSAT 2019. Learning and analytics in intelligent systems, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-030-42363-6_20
Kopanakis I, Pelekis N, Karanikas H, Mavroudkis T (2005) Visual techniques for the interpretation of data mining outcomes. In: Proceedings of the Panhellenic conference on advances in informatics, 2005, pp 25–35
Elkan C (2003) Using the triangle inequality to accelerate k-means. In: Proceedings of the international conference on machine learning, 2003, pp 147–153
Catanzaro B, Sundaram N, Keutzer K (2008) Fast support vector machine training and classification on graphics processors. In: Proceedings of the international conference on machine learning, 2008, pp 104–111
Zhang T, Ramakrishnan R, Livny M (1996) BIRCH: an efficient data clustering method for very large databases. In: Proceedings of the ACM SIGMOD international conference on management of data, 1996, pp 103–114
Haque H, Labeeb K, Riha RB, Khan MNR (2021) IoT based water quality monitoring system by using Zigbee protocol. In: 2021 international conference on emerging smart computing and informatics (ESCI), Pune, India, 2021, pp 619–622. https://doi.org/10.1109/ESCI50559.2021.9397031
Labeeb K, Chowdhury KBQ, Riha RB, Abedin MZ, Yesmin S, Khan MNR (2020) Pre-processing data in weather monitoring application by using big data quality framework. In: 2020 IEEE international women in engineering (WIE) conference on electrical and computer engineering (WIECON-ECE), Bhubaneswar, India, 2020, pp 284–287. https://doi.org/10.1109/WIECON-ECE52138.2020.9397990
Batistic S, Laken PVD (2019) History, evolution and future of big data and analytics: a bibliometric analysis of its relationship to performance in organizations. Br J Manag 30(2019):229–251
Khan MNR, Durdana WF, Roy R, Poddar G, Ferdous S, Mashuk AKEH (2018) Health guardian—a subsidiary android application for maintaining sound health. In: 2018 international conference on recent innovations in electrical, electronics & communication engineering (ICRIEECE), 2018, pp 1406–1409. https://doi.org/10.1109/ICRIEECE44171.2018.9008485
Khan MNR, Khan MR, Mashuk AKEH, Sunny FI, Farhan SKA, Shukhon RNS (2020) An android application to calculate the average chemical presence in food items. In: Dawn S, Balas V, Esposito A, Gope S (eds) Intelligent techniques and applications in science and technology. ICIMSAT 2019. Learning and analytics in intelligent systems, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-030-42363-6_16
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Khan, M.N.R., Tasnim, F., Yesmin, S., Abedin, M.Z. (2022). Review of City Pricing System Analysis Based on Big Data. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Bestak, R. (eds) Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-6460-1_25
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