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Time series
A new fuzzy time series model based on Hedge Algebra to forecast bitcoinThe fuzzy time series model has become a research topic attracting attention because of its practical value in the field of time series forecasting, specifically, it is useful for time series with small observations or the one of strong fluctuations. This paper introduces a fuzzy time series model based on hedge algebra with a new formula for calculating forecasting values.
Summary of Mathematics Doctoral Dissertation: Apply Markov chains model and fuzzy time series for forecastingThesis with the aim of focusing on two main issues. The first is time series modeling by states in which each state is a deterministic probability distribution (normal distribution). Based on the experimental results to assess the suitability of the model. Second, combine Markov chains and fuzzy time series into new models to improve forecast accuracy. Expand the model with high-level Markov chains to be compatible with seasonal data.
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A hybrid PSO-SA scheme for improving the accuracy of fuzzy time series forecasting modelsIn line with that research trend, this paper proposes a hybrid algorithm combining particle swarm optimization with the simulated annealing technique (PSO-SA) to optimize the length of intervals to improve forecasting accuracies.
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Time series analysis and applications in data analysis, forecasting and predictionTime series analysis is an essential field in data analysis, particularly within forecasting and prediction domains. Researching and building time series models play a crucial role in understanding and predicting the temporal dynamics of various phenomena. In mathematics, time series data is defined as data points indexed in chronological order and have a consistent time interval between consecutive observations.
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Doctoral thesis of Philosophy: Economic consequences of the size of government in AustraliaThe thesis contributes to the economics literature by providing a theoretical and empirical investigation of the effects of changes in the relative size of government on Australian economic performance. The theoretical literature indicates that an expansion in government size is likely to induce adverse effects upon economic growth for a host of reasons. These include the distortionary effects of taxation imposed to finance government expenditures, the displacement effects of private sector economic activity attributable to public sector interventions, and the growth in governmental activity encouraging economic participants to divert their attentions away from direct market activities and towards seeking benefits through the political process.
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Impact of capital market on Nigerian economy, 1981 - 2014This study examined the impact of the capital market on Nigerian economy. Time series data were collected on Real Gross Domestic Product, Market Capitalization, All Share Index and Turnover Ratio from 1981 - 2014.
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Machine learning applications for chloride ingress prediction in concrete: Insights from recent literatureThis review explores recent ML advancements in assessing corrosion in RC structures. Various algorithms, such as Artificial Neural Networks (ANNs), Gene Expression Programming (GEP), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM) and Ensemble Learning, have shown potential in estimating corrosion processes, predicting material properties, and evaluating structural durability.
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Short-term prediction of regional energy consumption by metaheuristic optimized deep learning modelsModern civilization is heavily dependent on energy, which burdens the energy sector. Therefore, a highly accurate energy consumption forecast is essential to provide valuable information for efficient energy distribution and storage. This study proposed a hybrid deep learning model, called I-CNN-JS, by incorporating a jellyfish search (JS) algorithm into an ImageNetwinning convolutional neural network (I-CNN) to predict weekahead energy consumption.
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Master's thesis of Business: Modelling dynamic financial linkages, spillover effects and volatility transmissions: empirical evidence from China and international financial marketsThe rationale for this study is that the social enterprise sector provides an important locale in which to situate research that aims to identify the impact of ICTs on development. Recognising the complex dynamics and range of actors involved in this diverse and emerging area of development practice, this study chooses to focus on the social enterprise sector. It is specifically concerned with mapping the external influences, use and impact of ICT on social enterprises in Cambodia. Examining the case of the social enterprise sector in one developing country, although descriptive in nature, fills an essential knowledge gap in the field of ICT and development.
228 trang
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Prospects of LSTM neural networks use in supply chain management when developing a crypto currency rate forecastThe research subject is the process of economic and mathematical modelling of time series characterizing the bitcoin exchange rate volatility, based on the use of artificial neural networks. The purpose of the work is to search and scientifically substantiate the tools and mechanisms for developing prognostic estimates of the crypto currency market development. The paper considers the task of financial time series trend forecasting using the LSTM neural network for supply chain strategies.
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Bài giảng Toán tài chính - Chương 7: Dãy số thời gian time seriesBài giảng "Toán tài chính - Chương 7: Dãy số thời gian time series" cung cấp cho người học các kiến thức: Định nghĩa, dùng chuỗi thời gian để dự báo, các thành phần của chuỗi thời gian, mô hình chuỗi thời gian,... Mời các bạn cùng tham khảo.
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