Study on Dynamic Evaluation of Sci-tech Journals Based on Time Series Model

Abstract

As science and technology continue to advance, sci-tech journals are developing rapidly, and the quality of these journals affects the development and progress of particular subjects. Whether sci-tech journals can be evaluated and predicted comprehensively and dynamically from multiple angles based on the current qualitative and quantitative evaluations of sci-tech journals is related to a rational adjustment of journal resource allocation and development planning. In this study, we propose a time series analysis task for the comprehensive and dynamic evaluation of sci-tech journals, construct a multivariate short-time multi-series time series dataset that contains 18 journal evaluation metrics, and build models based on machine learning and deep learning methods commonly used in the field of time series analysis to carry out training and testing experiments on the dataset. We compare and analyze the experimental results to confirm the generalizability of these methods for the comprehensive dynamic evaluation of journals and find the LSTM model built on our dataset produced the best performance (MSE: 0.00037, MAE: 0.01238, accuracy based on 80% confidence: 72.442%), laying the foundation for subsequent research on this task. In addition, the dataset constructed in this study can support research on the co-analysis of multiple short time series in the field of time series analysis.

Optimal Operation of Cogeneration Power Plant Integrated with Solar Photovoltaics Using DLS-WMA and ANN

“…Data are received by the input layer (α) and are then presented to the hidden layer. Here, the input data and corresponding weight values (wg) are represented in the following equations [33].…”

“…The output of the input layer is then passed into the hidden layer, which aggregates the weight and bias values and uses the rectified linear activation function (ReLU) activation function to train the input designs. Thus, the hidden layer is mathematically planned as in the following equations [33].…”

“…where wg i represents the weight values, Bias denotes the bias values initialized randomly, and I Act signifies the activation function. Here, the ReLU activation function activates the planned neurons, as in the following equation [33].…”

“…The weights of the input data are added together to determine the output unit. This unit is expressed by the following equation [33].…”

Research on the evaluation of academic journals from a multidimensional fusion measurement perspective

“…Journal evaluation is tackled from a diverse range of research perspectives that covers many dimensions, from single (Balatsky et al , 2021) to multidisciplinary (Han and Qiu, 2022) and cross-disciplinary analyses (Zhang et al , 2019). Traditional journals (Zheng et al , 2019) to open access publication (Wei, 2020), static (Hao and Li, 2019) to dynamic evaluation (Ma et al , 2022) and single factor (Abramo et al , 2023) to multidimensional information measurement (Wang, 2022), all have relevant studies regarding journal evaluation.…”