Technical Indicators Research Articles

Study of heat transfer and hydrodynamic processes in a full-size thermosyphon installation under the influence of solar radiation with coolant

Abstract This article discusses the theoretical background and results of the study of heat exchange and hydrodynamic processes occurring in a thermosiphon installation. One of the important characteristics of the operation of thermosiphons is their ultimate heat transfer capacity, the calculation of which allows us to create a reliable, highly efficient heat exchange device. For optimal design and improvement of the technical and economic indicators of a thermosiphon installation, it is necessary to develop and improve scientifically based methods for calculating the processes occurring in the elements of its design. The purpose of the experimental part of the work was to test the selected theoretical model and more accurately determine the physical picture of the processes occurring in full-scale thermosiphon installations by measuring not only integral, but also local characteristics of the installation. There is intense heating of the liquid in the collector in the first half of the day (from 11 to 13 hours) and a slowdown in the rate of increase in temperature at the outlet of the collector in the second half of the day. A drop in the level of solar radiation in the second half of the day does not lead to a significant decrease in the temperature at the outlet of the collector, which is obviously explained by an increase in the temperature of the liquid at the inlet to the collector during the period under consideration. The presence of a long period of lag in the increase in the temperature of the liquid at the inlet to the collector compared to the temperature at the outlet is associated with the inertia of thermal processes in the system. The time interval from the beginning of the experiment to the beginning of the increase in the temperature of the liquid at the inlet to the collector coincides with the period of a single circulation of the liquid in the system.

Direct endoscopic necrosectomy: Pilot study of a new dedicated device.

Background and study aims Direct endoscopic necrosectomy (DEN) represents the first-line treatment for walled-off necrosis (WON). However, DEN has a non-negligible rate of overall adverse events (AE) and is time-consuming due to the lack of dedicated devices. This pilot study was designed to evaluate the feasibility and safety of a novel dedicated device for DEN named Necrolit. Patients and methods In this multicenter retrospective analysis,16 patients with WON who underwent DEN using Necrolit were compared with a control group treated with non-dedicated devices. Technical success, AEs, clinical success, number of procedures per patient, procedure time, and length of hospital stay were evaluated. Necrolit technical performance indicators were also studied. Results Technical success was obtained in all patients in both groups. In the Necrolit group, the overall AE rate was 10.1% vs. 15.9% in the control group. Clinical success was 100% in the Necrolit group vs. 81.3% in the control group. Patients treated with Necrolit underwent a slightly lower mean number of procedures (4.1 ± 2.3 vs. 5.1 ± 1.9) with comparable mean procedure time (67.8 ± 39 minutes vs. 70.1 ± 32.6 minutes). Mean duration of hospital stay was 39.4 days (± 30.9) in the Necrolit group vs. 43 days (± 29.4) in the control group. Device-related technical performance was rated positively. Conclusions DEN with Necrolit appears feasible and safe.

Impact of virgin and recycled polymer fibers on the rheological properties of cemented paste backfill

The addition of polymer fibers to cemented paste backfill (CPB) has shown promise in enhancing mechanical properties, although it also introduces changes in rheological characteristics. This study aimed to investigate the influence of different types of polymer fibers, namely virgin commercial polypropylene fiber (CPPF), recycled tire polymer fiber (RTPF), and recycled tire rubber fiber (RF), on the rheological properties of CPB mixtures through an experimental program, and provide design references for CPB pipeline transport. The results revealed consistent reductions in bulk density upon the incorporation of polymer fibers into CPB, alongside varying impacts on slump. Specifically, the addition of CPPF had a mild effect, while RTPF caused a continuous decrease in slump, and RF exhibited minimal influence up to a 4% concentration, with substantial effects thereafter. Moreover, the inclusion of fibers led to increases in apparent viscosity parameters, with RTPF inducing the most significant changes, followed by varying responses from CPPF and RF. When using RTPF for CPB reinforcement, emphasis should be placed on enhancing technical indicators related to viscosity such as energy consumption and pipeline wear during pipeline transport. Furthermore, adjustments were necessary to account for flow curve instability resulting from interactions between fibers and the paddle, with the data aligning well with the Bingham model. The addition of fibers, particularly CPPF and RF, primarily influenced plastic viscosity rather than yield stress, underscoring the limitations of slump tests in assessing rheology.

The efficacy of Relative Strength Index (RSI) in KLSE market trade

The Relative Strength Index (RSI) is a widely used technical indicator in stock trading because of its simple application. However, its application combined with fundamental analysis in Kuala Lumpur Stock Exchange (KLSE) is yet to be explored extensively. Hence, this study aimed to investigate the effectiveness of RSI as a predictive tool in the KLSE market. First, 39 stocks that met the set of criteria guided by fundamental soundness were identified. Trading signals are then initiated based on the RSI indicators, which are superimposed on the charts of the identified stocks. The return on investment (ROI) was then estimated and benchmarked against KLCI performance over a period of five years starting from 21st July 21, 2018. It was found that the average ROI was 3.46% against KLCI’s -24.37% over the same period of 5 years, measured between 21st July 21, 2018, 21st July 21, 2023. The average ROI improves as the number of trade iterations increases to five. The peak average ROI is approximately 22%. Technology is the top performer, recording an ROI of more than 40%. In conclusion, the combination of RSI and fundamental analysis yielded a mixed set of results. Although it outperforms KLCI, the annualised ROI is only slightly above 4%. Nevertheless, the results of this study provide valuable insights into the application of the RSI as a trading signal generator in the KLSE market.

IMPROVED DECISION-MAKING ALGORITHM FOR THE REDEVELOPMENT OF INDUSTRIAL AREAS

Raising of problem. As a result of the financial and economic crisis, many industrial enterprises have ceased operations or significantly reduced production volumes due to the shrinking markets for their products, which is accompanied by destructive processes and phenomena. In a dynamic competitive environment, some enterprises have outdated and worn-out fixed assets, their products are not in demand, their premises are leased, large areas are covered with waste and harmful substances that are environmentally hazardous, low technological level of production, weak scientific and technical sphere, and reduced supply of labour resources. Therefore, ensuring sustainable development of Ukraine is impossible without solving the problems of restructuring and qualitative renewal of industrial production, reconstruction of degraded urban areas occupied by abandoned buildings and structures of industrial enterprises. Thus, there is an objective need to increase the level of profitability of land development by justifying alternative land use options: demolition of degraded industrial enterprises and construction of new facilities or reconstruction of industrial buildings and structures with a change of functional purpose. However, there is currently no unified approach to building an information model of the decision-making process for the reconstruction of industrial enterprises with a change in their functional purpose. Translated with DeepL.com (free version). Purpose of the aricle. To develop an improved decision-making algorithm for the reconstruction of mining enterprises with a change in functional purpose. Conclusion. The decision-making algorithm for the reconstruction of industrial enterprises with a change in functional purpose, which ensures the receipt of substantiated values of technical and economic indicators of such projects, depending on the available initial information about the object and the conditions of production of works, and also provides the possibility of specifying the values indicators of the effectiveness of managerial decisions at different stages of the life cycle, thanks to the adjustment of the values of the duration and cost of reconstruction by varying the parameters that are part of the determining factors.

RECONSTRUCTION OF THE SYSTEM OF GREENING TERRITORIES OF THE DNIPRO AREA IN THE MINDS OF FURTHER TRANSFORMATIONS OF EXOGENIC, ENDOGENIC AND ANTHROPOGENIC FACTORS OF THE OLD DEVELOPMENT

Raising of problem. As a result of the financial and economic crisis, many industrial enterprises have ceased operations or significantly reduced production volumes due to the shrinking markets for their products, which is accompanied by destructive processes and phenomena. In a dynamic competitive environment, some enterprises have outdated and worn-out fixed assets, their products are not in demand, their premises are leased, large areas are covered with waste and harmful substances that are environmentally hazardous, low technological level of production, weak scientific and technical sphere, and reduced supply of labour resources. Therefore, ensuring sustainable development of Ukraine is impossible without solving the problems of restructuring and qualitative renewal of industrial production, reconstruction of degraded urban areas occupied by abandoned buildings and structures of industrial enterprises. Thus, there is an objective need to increase the level of profitability of land development by justifying alternative land use options: demolition of degraded industrial enterprises and construction of new facilities or reconstruction of industrial buildings and structures with a change of functional purpose. However, there is currently no unified approach to building an information model of the decision-making process for the reconstruction of industrial enterprises with a change in their functional purpose. Translated with DeepL.com (free version). Purpose of the aricle. To develop an improved decision-making algorithm for the reconstruction of mining enterprises with a change in functional purpose. Conclusion. The decision-making algorithm for the reconstruction of industrial enterprises with a change in functional purpose, which ensures the receipt of substantiated values of technical and economic indicators of such projects, depending on the available initial information about the object and the conditions of production of works, and also provides the possibility of specifying the values indicators of the effectiveness of managerial decisions at different stages of the life cycle, thanks to the adjustment of the values of the duration and cost of reconstruction by varying the parameters that are part of the determining factors.

VADER SENTIMENT ANALYSIS ON TWITTER: PREDICTING PRICE TRENDS AND DAILY RETURNS IN INDIA’S STOCK MARKET

The study explores the effectiveness of sentiment analysis in predicting stock price movements, specifically focusing on the Indian Stock Market. The study investigates the reliability of social media sentiment analysis in financial markets and its implications for investors and traders. The research utilizes a sample of Twitter data comprising tweets containing hashtags related to the State Bank of India (SBI), used as a representative sample of the broader Indian Stock Market, collected from January 2021 to February 2024. The Valence Aware Dictionary for Sentiment Reasoning (VADER) algorithm was employed to analyse the sentiment of the Twitter data. Machine learning methods, including Random Forest, XGBoost, and AdaBoost, were used to integrate sentiment scores with technical indicators for predicting stock price trends. The results reveal that using only sentiment analysis achieved an accuracy of around 60% in predicting stock price direction. However, this accuracy increased to 70% with the AdaBoost method, 79% with the XGBoost method, and 82% with the Random Forest method combined with technical indicators while increasing the F1 scores from 0.4 to 0.8 in all three methods. Integrating sentiment analysis with technical indicators enhances financial market predictions by combining real-time investor sentiment with empirical historical data, leading to more accurate and adaptive trading strategies. Sentiment score was found to have a strong positive correlation with positive daily returns compared to negative daily returns, indicating that higher positive sentiment is associated with increased returns. Although negative sentiment exhibits a statistically significant correlation with daily returns, it shows a weaker positive association.

Assessment of hydrogen production technologies from agricultural residues in Vietnam

Green hydrogen is one of the alternative options to decarbonize the energy sector and limit the global temperature rise below 1.5 °C. Vietnam has various biomass resources, including agricultural and forestry by-products. However, this country has not had any research to evaluate the suitability of hydrogen production technologies using biomass sources in general and agricultural residues in particular with all relevant factors as a basis for investment and development. The paper assesses three green hydrogen production technologies from agricultural residue, including pyrolysis, gasification, and fermentation, by simultaneously applying the Strength Weakness Opportunity Threat (SWOT) analysis and Analytic Hierarchy Process (AHP). The hydrogen production technologies and agricultural residues in Vietnam are used as case studies. The obtained results on the weighting factors indicate that the economic indicator accounts for 50.7 %, followed by the technical indicator at 27.8 % and the environmental indicator at 21.5 %. Among the hydrogen production technologies, gasification is the most prioritized technology, at 43.3 %. The priorities of pyrolysis and fermentation are not considerably different, at 29.6 % and 27.1 %, respectively. Rice straw has the highest hydrogen production capacity with a total potential of about 50.43 billion m3 while the lowest total hydrogen production potential is cassava pomace with a value of 0.26 billion m3. Designing and simulating the hydrogen production process from agricultural waste using selected technologies will be studied in further work to finalize and verify the used assumptions, methods, and information in this study.

Identification and application of indicators for the assessment of pumped hydro storage projects with renewable energy generation

Pumped hydro storage is crucial in Europe's energy strategy to achieve a 100% renewable energy-based electricity system by 2050. As a consequence of the large number of factors involved and the variety of criteria included in a proper assessment of renewable generation projects with pumped hydro storage, this paper aims to identify and calculate technical, economic, environmental and social indicators in order to provide a tool to improve the decision-making process in this type of large-scale projects.

Thermal Deformation Measurement of the Surface Shape of a Satellite Antenna Using High-Accuracy Close-Range Photogrammetry.

To determine both the size of a satellite antenna and the thermal deformation of its surface shape, a novel high-accuracy close-range photogrammetric technique is used in this study. The method is also applied to assess the performance of the antenna in orbit. The measurement principle and solution method of close-range photogrammetry were thoroughly investigated, and a detailed measurement test scheme was developed. A thermal deformation measurement of the surface shape of a satellite antenna was then carried out. The results show that the measurement error using close-range photogrammetry was smaller than 0.04 mm, which meets the accuracy requirement. Thanks to the high accuracy, it was discovered that both the surface shape and the rib precision of the satellite antenna deteriorate with decreasing temperature. The accuracy of the surface shape and ribs was lowest when the temperature node was -60 °C. The maximum root mean square errors (RMSEs) reached 0.878 mm and 0.761 mm, respectively. This indicates that the surface shape deformation error of the antenna caused by high and low temperatures is relatively high. However, the requirement for the technical design index (RMSE ≤ 1 mm for the surface shape accuracy of the antenna) is still met. Furthermore, for temperature differences of 40 °C and 80 °C, the measured RMSEs for the surface shape deformation were 0.216 mm and 0.411 mm, respectively. Overall, the technical design indicators (RMSE ≤ 0.3 mm and RMSE ≤ 0.5 mm, respectively) for the surface shape deformation of the antennas are met.

Chaos, overfitting and equilibrium: To what extent can machine learning beat the financial market?

In this paper, we applied 10 technical analysis indicators to predict stock price movement directions using support vector machines, investigating the effects of hyperparameter variations on the out-of-sample classification performance and the profitability of the resulting trading strategies. We collected daily data between January 1st, 2018, and March 31st, 2023 for the 30 firms that compose the Dow Jones Industrial Average (DJIA). Our results indicated that the out-of-sample accuracy converged to 50%, while a small percentage (13.63% for the pre-COVID period and 23.16% for the post-COVID period) of the hyperparameter combinations yielded gains above the buy-and-hold strategy; on the other hand, no clear patterns about the best-performing hyperparameter combinations emerged, as the behavior of the out-of-sample performance was found to exhibit high sensitive dependence to the hyperparameters settings in comparison to its in-sample counterpart. The outcomes of our empirical analysis are consistent with both classic results in the finance literature (such as the Efficient Market Hypothesis) and empirical setbacks commonly seen in machine learning experiments, notably the occurrence of overfitting under the incorporation of high-dimensional non-linear interactions.

Non-pillar mining of upper coal seam layers with double-roadway driving using a flexible-formwork pre-cast partition wall

Abstract When mining layered coal seams, three-soft coal seams, high-gas coal seams, or hard-roof coal seams with the application of gob-side entry retention technology, various practical problems that seriously threaten construction safety arise, such as roadway deformation, shear failure of the roadway supporting body, and air leakage in the goaf. To effectively address these issues, in this work, a novel, pillar-free, coal mining technique based on a flexible-formwork pre-cast partition wall was proposed and applied to a case study: working face 2301 (upper) at Yuecheng Coal Mine, China. The principles of the technique and the characteristics of the movement in the surrounding rock were comprehensively examined. Through theoretical analysis and numerical simulation, the support parameters of the roadway and flexible-formwork pre-cast partition wall were determined and applied in the case study. From our analysis, it was demonstrated that the parameters of the flexible-formwork pre-cast partition wall and roadway support are reasonably designed, achieving effective roadway retention. Combined with a top cutting and pressure relief process, the roadway deformation can be eventually stabilised with the mining of the working face and does not affect the subsequent use of the roadway. From the acquired data, a good agreement between the field real-time measurements and the numerical simulation software measurements was found, which is helpful for the analysis of technological perspectives of the proposed framework. The introduced technology can effectively solve the technical problems existing in the traditional gob-side entry retention. It can not only realize non-pillar mining, but also double-roadway driving without coal pillars in 2301 working face can be achieved, which significantly improves the technical and economic index of the mine.

Predicting oil prices: A comparative analysis of machine learning and image recognition algorithms for trend prediction

This paper investigates the effectiveness of machine learning algorithms, including logistic regression, artificial neural networks, support vector machines, gradient boosting algorithms (XGBoost, ExtraTrees), random forests, and convolutional neural network (CNN) for trend prediction of daily spot oil prices across horizons of 1 to 8 days. We utilize a comprehensive set of features, including technical indicators, financial data, and volatility measures, to predict trends in closing prices. Our results reveal that the CNN model significantly outperforms other algorithms. This superior performance likely stems from CNN’s ability to capture visual patterns in price movements, potentially mimicking how traders identify trends.

Sustainable urban transformations based on integrated microgrid designs

The impacts of natural hazards on infrastructure, enhanced by climate change, are increasingly more severe emphasizing the necessity of resilient energy grids. Microgrids, tailored energy systems for specific neighbourhoods and districts, play a pivotal role in sustaining energy supply during main grid outages. These solutions not only mitigate economic losses and well-being disruptions against escalating hazards but also enhance city resilience in alignment with Sustainable Development Goal (SDG) 11. However, disregarding socioeconomic factors in defining microgrid boundaries risks perpetuating inequalities and impeding progress towards other SDG 11 targets, including fair democratic participation. Our approach integrates social and technical indicators to bolster urban microgrid planning. Through a case study in a US county, we illustrate how integrated microgrid planning effectively intertwines urban resilience, well-being and equity while promoting sustainable development. This study underscores the importance of integrated microgrid planning for sustainable and resilient urban transformation amid environmental and societal challenges.

Quality of public transport services in Chisinau

The quality of transport services represents the most comprehensive and synthetic attribute that reflects the performance of a transport system. In the public transport system, the quality of service is largely influenced by the way passengers perceive its performance. The quality of transport services is assessed according to a number of technical and economic indicators that characterize the performance of transport operators within the framework of the urban public transport system. The article aims to identify the criteria for evaluating the quality of urban public transport services based on the study carried out for the public transport system of the municipality of Chisinau and to describe the indicators that reflect the performance offered by the public transport system, as perceived by passengers. It should be noted that the quality of the urban public transport service has a direct impact on the quality of life of all city residents. The study includes a concrete survey of the beneficiaries of public transport in the municipality of Chisinau, which analyzes the quality criteria and their rate of appreciation by the inhabitants of the municipality. Finally, conclusions and future directions of action aimed at improving the quality of services and increasing the attractiveness of urban public transport are presented, thus contributing to the improvement of the quality of life of the inhabitants.

Formation of methodological foundations for the analysis of national development in conditions of foreign economic discrimination

Purpose: is to form a conceptual approach to the analysis of the macroeconomic effects of external sanctions based on increasing the information content of the use of technical indicators in assessing the stability and vulnerability of the national economy to the effects of discriminatory restrictions in foreign economic activity. Methods: the study is based on the processing and analysis of data obtained as a result of content analysis of a significant number of scientific, scientific-practical, and expert sources of information.Methods of scientific generalization and classification, economic, expert and statistical analysis were used.Results: the analysis of the impact of sanctions restrictions on the key indicators of the characteristics of sustainable and innovative development of the discriminated national economy is carried out. An approach to assessing the impact of sanctions is presented based on a conjugate analysis of the dynamics of target groupings of indicators. An example of calculations, visualization and interpretation of the results of assessing sanctions resistance and export-import dependence of the national economy based on a set of technical indicators for significant areas of socio-economic development of the discriminated country is illustrated. The scope of application of the proposed approach in the formation of the development strategy and program (in terms of the implementation of the process of import substitution, ensuring technological independence and structural adaptation of the economy) is justified, taking into account the risks of sanctions restrictions.Conclusions and Relevance: the proposed approach to the analysis of sanctions restrictions based on the combined use of technical criteria for the dynamics of grouped indicators provides an increase in the reliability of estimates of their negative impact. However, aggregated estimates do not allow us to justify selective and targeted measures aimed at adapting the institutional and organizational conditions of the activities of specific economic agents in key areas of the national economy. A possible direction for further research may be the development of methodological and analytical tools for assessing the sanctions stability of economic sectors to substantiate the priorities of ensuring their technological independence.

Optimum management of microgrid generation containing distributed generation sources and energy storage devices by considering uncertainties

In recent years, the financial and energy crises have made the economical and safe operation of distribution microgrids one of the main challenges for operators. In this regard, the optimal distribution of the microgrid, considering the favorable indicators of Generation and consumption, significantly improves the quality of the development and economic operation of electricity grids. On the other hand, distribution microgrids have many problems and complications due to the presence of DG sources and the uncertainties caused by them in Generation and consumption, such as the inability to solve optimal load distribution using common and common calculation methods. Therefore, grid technical indicators such as voltage deviation and losses in solving load distribution add to the complexity of related issues. To solve the challenges raised in the distribution microgrid, this paper proposes an optimal load distribution model that models the uncertainties in the distribution microgrids using the Monte Carlo method. Using meta-heuristic algorithms, the optimal Generation function by modeling grid security constraints such as voltage deviation, losses, and a load limit of the system should be in economic operation mode, and then the power distribution equations should be solved. The battery can supply 1 kW of active power to the system at a cost of 1 unit/kW during the high cost period if it absorbs 1 kW of active power at a cost of 0.92 units/kW during the low cost period. Additionally, the active and reactive power losses have been decreased to 0.3kW and 0.2kW, respectively, by utilizing the suggested methodology. The simulation results show that the proposed method performs satisfactorily and that the modeling is simulated in MATLAB software.

Enhancing the accuracy of stock return movement prediction in Indonesia through recent fundamental value incorporation in multilayer perceptron

PurposeThe study aims to explore how integrating recent fundamental values (RFVs) from conventional accounting studies enhances the accuracy of a machine learning (ML) model for predicting stock return movement in Indonesia.Design/methodology/approachThe study uses multilayer perceptron (MLP) analysis, a deep learning model subset of the ML method. The model utilizes findings from conventional accounting studies from 2019 to 2021 and samples from 10 firms in the Indonesian stock market from September 2018 to August 2019.FindingsIncorporating RFVs improves predictive accuracy in the MLP model, especially in long reporting data ranges. The accuracy of the RFVs is also higher than that of raw data and common accounting ratio inputs.Research limitations/implicationsThe study uses Indonesian firms as its sample. We believe our findings apply to other emerging Asian markets and add to the existing ML literature on stock prediction. Nevertheless, expanding to different samples could strengthen the results of this study.Practical implicationsGovernments can regulate RFV-based artificial intelligence (AI) applications for stock prediction to enhance decision-making about stock investment. Also, practitioners, analysts and investors can be inspired to develop RFV-based AI tools.Originality/valueStudies in the literature on ML-based stock prediction find limited use for fundamental values and mainly apply technical indicators. However, this study demonstrates that including RFV in the ML model improves investors’ decision-making and minimizes unethical data use and artificial intelligence-based fraud.

Научно-методический подход к разработке проектов опытно-промышленных испытаний открытой разработки месторождений

Methodology of designing pilot tests in open-pit mining is a complex and insufficiently developed issue in the theory and practice of designing mining systems, which, as a rule, fails to take into account the mining and geological features of the deposits. The complex development of mineral deposits requires new methods of open-pit designing. Thus, the theoretical justification and development of the methods to determine the optimal parameters and indicators of open-pits during the design of pilot tests with the establishment of scales, deadlines, tasks and test conditions is an urgent research problem. The authors of the study have systematized the research trends in developing the basis for designing pilot tests in open-pit geotechnology. The level of geological inaccuracies in case of insufficiently reliable prospecting results leads to a decrease in the expected technical and economic indicators of the mining project ranging from 5-20% to several folds. When information on the deposit is insufficient, pilot test projects are prepared. This is done in order to obtain additional input data for preparation of the feasibility study of permanent conditions or at the stage of the field development to verify the created technologies and means of their mechanisation in order to avoid revision of the mining system parameters in the course of the field operations due to discrepancies between the geomechanical and hydrogeological representations given in the detailed exploration materials and the real conditions.

Developing A Piano Teaching Model for Music Majors in Chinese Higher Education and Improving Student's Piano Playing Skills

China's economic and social development, cultural industry progress, and improved living standards have led to a diversified society for piano professionals and applied talents. This study aimed to analyze the piano teaching mode in higher schools. Explore the existing piano teaching modes at home and abroad, and analyze the characteristics, advantages, and shortcomings of different teaching modes and evaluate the new piano teaching mode and verify its effect of improving students' piano playing application ability. The current study clarified the related implications under the initial dimensions for a follow-up particular analysis by examining the syllabi of piano teaching models from five universities' music programs using the Research & Development (R&D) theoretical framework. The study examines and contrasts relevant research on domestic piano instruction models through a survey of the literature. This stage seeks to categorize and condense the findings of previous research, comprehend the theoretical underpinnings and real-world application of applied talent training models both domestically and internationally, and offer a theoretical framework and point of reference for this investigation. This study employs various research tools, including literature analysis, structured questionnaires, observation forms, and checklists, to collect comprehensive data to address the research questions. It explored that teaching methods: at present, China's higher education piano teaching methods are diverse, emphasis on skills training, ignoring the cultivation of music literacy. In the process of teaching, teachers tend to focus on demonstration, and students have fewer opportunities to practice, which leads to the lack of students' innovative ability. The Curriculum: China's higher education piano teaching is based on professional courses, and a small number of elective courses in the curriculum to assist. As a result, the content of the curriculum is relatively single and lacks the cultivation of students' comprehensive ability. The Evaluation system: China's higher education piano teaching is mainly based on performance examination, which overly emphasizes technical indicators and neglects musical expression and creativity. In addition, the evaluation standard is too uniform, making it difficult to meet students' individual needs.