In recent years, with the rapid development of the domestic economy, the concept of sustainable development has been paid more and more attention. Ecological environment protection is more and more important, and the ecological environment is closely related to economic development. How to measure the relationship between the two is very important. Whether it is to build ecological environment protection or to ensure sustainable development of the economy, we should take the green development concept as a guiding concept, promote ecological economic development, and study the integration of ecological data is of great significance for solving these problems. The research of this thesis studies the multi-source heterogeneous (MSH) ecological big data (BD)adaptive fusion based (FM) based on symmetric encryption. This paper sets up a comparative experiment, multi-sensor (MS) data fusion based (DFM) based on Rough set theory, MSH data fusion based on data information conversion. The method is compared with the symmetric fusion MSH BD adaptive FM proposed in this paper. The results show that the MSH DFM based on Rough set theory has the highest confidence of 0.812; the MSH DFM based on data information conversion has the highest confidence of 0.68; based on symmetric encryption MSH BD The fusion confidence of the adaptive FM is up to 0.965, and the MSH ecological BD adaptive FM based on symmetric encryption is superior.
Read MoreDoi: https://doi.org/10.54216/FPA.050101
Vol. 5 Issue. 1 PP. 08-20, (2021)
Intangible cultural heritage is the continuous progress of human society. Intangible cultural heritage refers to various traditional cultural expressions that exist in intangible form and are closely related to the lives of the people and inherited from generation to generation. Intangible cultural heritage is a human-oriented living cultural heritage. It emphasizes human-centric skills, experience, and spirit, and is characterized by living changes. What stands out is the intangible attribute, and more emphasis on the quality that does not depend on the material form. The biggest feature of intangible cultural heritage is that it is not divorced from the special life and production methods of the nation, and it is the "living of the nation's personality and national aesthetic habits. "Appears. It exists on the basis of human beings, using voice, image and skills as means of expression, and passing from word to mouth as a cultural chain to continue. It is the most vulnerable part of "living" culture and its traditions. Therefore, for the process of inheriting intangible cultural heritage, the inheritance of people is particularly important. The traditional handicraft intangible cultural heritage is one of the best. However, with the rapid development of society, the living environment of intangible cultural heritage has changed, and the intangible cultural heritage of traditional handicraft industry is rapidly declining or even disappearing. In order to protect traditional handicraft intangible cultural heritage, this article studies the influence of the integration of traditional handcrafted intangible cultural heritage with the form of material carrier, reading and analyzing a large number of related documents using the literature survey method, and according to research needs, through the study of the content of the literature In summary, a questionnaire survey method was adopted to investigate traditional handicraft intangible cultural heritage visitors and inheritors. The results of the survey found that visitors’ satisfaction with the integration of digital forms and physical carrier forms of intangible cultural heritage projects was nearly 30% higher than that of unintegrated forms. Inheritors generally believe that integrated research has better publicity and education for traditional handicraft intangible heritage. The merged handmade intangible cultural heritage items are easy to store, retrieve and query, and at the same time help to preserve the related traditional handmade intangible cultural heritage items safely and for a long time, making the traditional handmade intangible cultural heritage items widely spread and shared around the world.
Read MoreDoi: https://doi.org/10.54216/FPA.050102
Vol. 5 Issue. 1 PP. 21-30, (2021)
Bitcoin is one of the primary computerized monetary forms to utilize peer innovation to work with moment installments. The free people and organizations who own the overseeing figuring control and take part in the bitcoin network—bitcoin "miners"— are accountable for preparing the exchanges on the blockchain and are persuaded by remunerations (the arrival of new bitcoin) and exchange charges paid in bitcoin. These excavators can be considered as the decentralized authority implementing the believability of the bitcoin network. New bitcoin is delivered to the excavators at a fixed yet occasionally declining rate. There is just 21 million bitcoin that can be mined altogether. As of January 30, 2021, there are around 18,614,806 bitcoin in presence and 2,385,193 bitcoin left to be mined. This paper will predict the nature of bitcoin price because according to the reports of the past few years. The year 2020-present appeared to be a good time for bitcoin because, during this time duration, bitcoin has seen huge ups and downs. This paper will use various Machine Learning Techniques for the predictive analysis of bitcoin to accurately predict the price's nature. As the price of bitcoin depends upon various factors, and these factors directly affect the price, i.e., multiple factors of bitcoin are dependent on each other. After analyzing the results from multiple research papers and review papers, we discovered each algorithm has its advantages and disadvantages when predicting the bitcoin value. Keeping in mind all the findings, we will find algorithms that predict the bitcoin price accurately and without fewer disadvantages. So, if we go as per assumptions, regression would be the best choice for predicting the bitcoin value, but there are others algorithms also. So, in this paper, we will see the results of the multiple algorithms and then choose the correct algorithm after analyzing the results of all the implemented algorithms. This paper also includes the implementation of the comparison charts with each algorithm so that it will be easy to analyze the findings of each algorithm.
Read MoreDoi: https://doi.org/10.54216/FPA.050103
Vol. 5 Issue. 1 PP. 31-41, (2021)
Optimizing efficiency studies were carried out to comply with environmental norms by using MCDM techniques to pick low GWP refrigerants for automotive air conditioning. Multi-criteria optimization for time consumption based on ratio analysis plus full multiplicative form (MULTIMOORA), is being employed in this work to compare 10 distinct alternatives with 10 criteria. Thermal conductivity, vapor pressure, saturation fluid density, latent specific heat, fluid viscosity, GWP, ozone-depleting potential, and cost per pound are among the many response qualities suited for data acquisition in terms of thermodynamics, and environmental stewardship, and economics. It is possible to standardize decision-makers grading and weighting systems using MCDM methodologies. RAA3 had the greatest rank among the 10 refrigerants tested in the MULTIMOORA methodology. The EDAS and TOPSIS techniques identified R-744 to be the worst refrigerant, whereas the MOORA approach showed RAA5 to be the worst refrigerant.
Read MoreDoi: https://doi.org/10.54216/FPA.050104
Vol. 5 Issue. 1 PP. 42-50, (2021)