Using transformer to predict the price of commodity by Zhou, Siyu

“…In this study, we explored the use of the Transformer model for time serial prediction and applied it to commodity price prediction, particularly for specific commodities and gold prices in the market. …”
Get full text

Housing price prediction using machine learning by Tan, Yawen

“…Predicting the housing price is an enduring topic since the price change of real estate has a great relationship with the economy, policy, and market. …”
Get full text

Optimized electric vehicles charging strategy based on differential evolution (DE) algorithm by Zhao, Zekai

“…This framework incorporates real-time pricing (RTP) mechanisms and Vehicle-to-Grid (V2G) technology to mitigate charging cost. …”
Get full text

Peer-to-peer transactive energy trading enabled decentralized energy management of a hybrid building cluster by Ying, Chenhao

“…To preserve the privacy and autonomy of each entity within the building cluster, a distributed algorithm incorporated with an efficient P2P pricing mechanism is designed for the formulated MLMF Stackelberg game problem. …”
Get full text

Operation and energy management of hybrid AC/DC building microgrid by Guan, Shaokang

“…There are two main factors which have a great impact on energy management system. One is dynamic pricing of electricity market. Different prices will directly influence the energy management decisions of microgrids. …”
Get full text

Using AI and big data to predict stock market by Li, Jing

“…Meanwhile, Machine Learning techniques, especially Deep Learning models are being applied for making stock price prediction for both classification task, which aims at predicting the price trend (upward or downward), and regression task trying to predict the exact price value. …”
Get full text

Deep neural networks for stock forecasting by Gao, Kexin

“…However, due to the uncertainty and nonstationarity of the stock series, forecasting stock price has become a big challenge. The emergence of neural network enables people to effectively train and predict the long-term correlated nonlinear time series. …”
Get full text

Reinforcement learning based smart home energy management by Li, Yiman

“…This thesis discusses how to perform energy control for smart homes, which is divided into three main parts: 1) Prediction of future electricity price based on LSTM algorithm. A more accurate electricity price is the basis for subsequent energy control of home appliances. 2) Modeling of various household appliances and energy management algorithms with different operational characteristics in smart homes. 3) The modeling of the smart home optimization problem and the development of a home energy management algorithm based on reinforcement learning. …”
Get full text

Stock forecasting using transformers by Peng, Xiaoqi

“…To obtain the investment value of stock more accurately, the technical analysis method of predicting the future stock price based on the past stock price and the fundamental analysis method based on the past intrinsic value of stocks (Composite Index, earnings per share, Market capitalisation in circulation) are adopted. …”
Get full text

Machine learning for value investing by Jin, Zhenyu

“…Through the analysis of the annual financial data (revenue, profit, assets, liabilities and other financial indicators) of thousands of listed companies by using ridge regression, aim to predict the future stock price of enterprises. Through in-depth analysis of ten years of financial data of these companies, we not only verify the correlation between financial characteristics and future stock prices, but also confirm the feasibility of machine learning models in the field of value investing. …”
Get full text

Develop a partial discharge data acquisition board in power grid by Liu, Peiran

“…The online test of the partial discharge of the high voltage electric equipment is usually based on these weak phenomena. Since the price of data acquisition boards on the market is very high, a data acquisition board with a simple structure is designed in this paper, which can achieve most functions while achieving a lower price. …”
Get full text

On-chip mid-infrared thermal emitter for filter-free gas sensing by Ma, Yixuan

“…With smaller volume and cheaper price, it still has great research value.…”
Get full text

AI-based smart home energy management by Zhou, Xueni

“…Then, the methodology on forecasting electricity price is mentioned, such as data collection and pre-processing techniques. …”
Get full text

Why sanctions on Russia did not work well? Russia's economic resistance against the sanctions in 2022 by Zhang, Xuan

“…Despite these preconditions that existed before the imposition of the sanctions, some new dynamics like high oil prices, strong exchange rates, and increasing ties with non-sanction states, also emerged in 2022’s sanctions on Russia and play a significant role in the mitigation of sanctions.…”
Get full text

Trash to treasure: harnessing resources from biogas & biomass power plants project #5: comparative farming costs analysis in Asia & Europe by Qiu, Zhongjian

“…In the end, an appropriate price of the waste-derived products is suggested after investigating the market.…”
Get full text

Stock market prediction using artificial intelligence by Zhang, Yiran

“…This work is divided into two sections, the first of which is a natural language processing module that analyzes sentiment for corresponding financial news, and the second of which is a stock prediction module that uses the output of the first module and past stock data to forecast future stock prices. This structure can more precisely forecast the stock's future trajectory. …”
Get full text

Virtual power plant in Singapore's electricity market by Lu, Qiaoying

“…These challenges include predicting renewable power and electricity prices in Singapore’s unpredictable climate, modeling VPPs that are suitable for typical HDB and commercial buildings with widely used air-conditioner systems in Singapore, and establishing the VPP participation model in Singapore’s unique electricity market. …”
Get full text

Future power system energy management for zero carbon emissions by You, Zheyu

“…The low-carbon penalty factor is a simplified idea which is set to change the generation price of different kinds of generators. 'Matpower' tool is used to simulate and compare the optimal solution of power system operation. …”
Get full text

Energy management of hybrid electric and thermal energy system by Hao, Xi

“…Coordination of electricity and thermal is crucial to save energy, reduce energy prices and achieve global emission targets. Against this background, the formation of a reliable and efficient operation scheme considering the relaxation of heating and cooling demand and the response characteristics of users is a problem that needs to be solved in the current development of integrated energy systems. …”
Get full text

Portfolio selection using feature selection approach by Dai, Zerui

“…Security market provides huge amount of historical data with respect to tradings, such as closing price and volume. As a result, risk measurement and criterion to evaluate a portfolio can be diversified according to investors considerations. …”
Get full text