9 research outputs found
Improved BIGRU Model and Its Application in Stock Price Forecasting
In order to obtain better prediction results, this paper combines improved complete ensemble EMD (ICEEMDAN) and the whale algorithm of multi-objective optimization (MOWOA) to improve the bidirectional gated recurrent unit (BIGRU), which makes full use of original complex stock price time series data and improves the hyperparameters of the BIGRU network. To address the problem that BIGRU cannot make full use of the stationary data, the original sequence data are processed using the ICEEMDAN decomposition algorithm to derive the non-stationary and stationary parts of the data and modeled with the BIGRU and the autoregressive integrated moving average model (ARIMA), respectively. The modeling process introduces a whale algorithm for multi-objective optimization, which improves the probability of finding the best combination of parameter vectors. The R2, MAPE, MSE, MAE, and RMSE values of the BIGRU algorithm, ICEEMDAN-BIGRU algorithm, MOWOA-BIGRU algorithm, and the improved algorithm were compared. An average improvement of 14.4% over the original algorithm’s goodness-of-fit value will greatly improve the accuracy of stock price predictions
Assessment of Aquatic Ecological Health Based on the Characteristics of the Fish Community Structures of the Hun River Basin, Northeastern China
Long-term ecological restoration can restore aquatic ecosystems to a certain extent and alleviate the crisis of freshwater fish biodiversity. In order to explore the fish community distribution patterns and key factors after ecological restoration and the health status of the watershed, fish and environmental data were collected from 39 sampling points in the Hun River Basin in the spring and autumn of 2021. A total of 51 fish species belonging to 11 families and 37 genera were collected during the survey, and the dominant species were Rhynchocypris lagowskii, Zacco platypus, Carassius auratus and Pseudorasbora parva. Compared with the results of past studies, the number of fish species has increased. The study found that the distribution of fish along the longitudinal gradient of the watershed showed obvious spatial differences and was divided into two groups. The results of canonical correspondence analysis (CCA) showed that agricultural land, urban land and grassland were the key factors for the spatial variation in fish communities in the Hun River Basin. The results of the F-IBI evaluation showed that the health status of the Hun River was fair or above fair, among which healthy, good, fair, poor and bad points accounted for 5.13%, 30.77%, 33.33%, 25.64% and 5.13%, respectively. The upper and middle reaches of the Hun River Basin were in better health, while the lower reaches were in poorer health, which was mainly affected by the intensity of human activities in different regions. This study will help watershed managers to make targeted restoration and protection measures for different regions
Study on the Basic Characteristics of Iron Ore Powder with Different Particle Sizes
In order to study in depth the differences in basic characteristics between iron ore fines commonly used by a steel company, and guide the sintering performance plant to choose the best ore allocation method, experimental studies on the basic characteristics of seven iron ore powders of three sizes were carried out using micro-sintering equipment, mainly including assimilation properties, liquid phase fluidity, and bonding phase strength. The results of the research showed that with the increase of the iron ore powder particle size, the assimilation of the seven iron ore powders showed an overall decreasing trend, deteriorating fluidity and decreasing bonding phase strength. Among them, the overall fluidity of iron ore powder A was poor, and the fluidity of iron ore powder B varied greatly between different particle grades, and the fluidity of iron ore powder C was more balanced and its bonding phase strength was high, while the overall bonding phase strength of iron ore powders B and E was low. The results of the study provide a theoretical basis for optimal ore allocation in sintering plants
Research on prediction model of iron ore powder sintering foundation characteristics based on FOA-Catboost algorithm
Sintered ore is the most important incoming iron material for blast furnaces in China. The foundation characteristics of sintering are an important basis for the sintering process of iron ore powder and a key indicator for evaluating the quality of iron ore powder. The chemical composition of iron ore powder directly affects the foundation characteristics of sintering. Based on the chemical composition and sintering characteristics of iron ore powder, the article adopts the FOA-Catboost algorithm to establish a prediction model for the foundation characteristics of single iron ore powder and mixed iron ore powder. Among the foundation characteristics prediction indicators of a single type of iron ore powder, the accuracy of assimilation temperature prediction is 95.65 %, the accuracy of fluidity index prediction is 95.23 %, and the accuracy of bonding phase strength prediction is 97.46. Among the foundation characteristics prediction indicators of mixed iron ore powder, the accuracy of assimilation prediction is 95.82 %, the accuracy of fluidity index prediction is 91.66 %, and the accuracy of bonding phase strength prediction is 93.7 %. On the basis of predicting the foundation characteristics of a single type of iron ore powder, the model further predicts the foundation characteristics of mixed iron ore powder, which can reduce the workload of laboratory experiments on the foundation characteristics of iron ore powder and reduce the amount of experiments in the process of finding the optimal proportion of mixed ore. Based on the foundation characteristics model of mixed ore, determine the optimal ratio of sintered ore powder to improve the quality of sintered ore. The establishment of the model has a significant contribution to improving experimental and production efficiency, reducing costs, improving sinter quality, and reducing environmental impact
Sulforaphane attenuates irradiation induced testis injury in mice
ABSTRACTObjective: The testis is vulnerable to ionizing radiation, sexual dysfunction and male infertility are common problems after local radiation or whole-body exposure. Currently, there are no approved drugs for the prevention or treatment of radiation testicular injury. Sulforaphane (SFN) is an indirect antioxidant that induces phase II detoxification enzymes and antioxidant genes. Herein, we investigated the radiation protective effect of SFN on testicular injury in mice and its potential mechanism.Materials and Methods: Mice were randomly divided into blank control group (Ctrl), radiation + no pretreatment group (IR), and radiation + SFN groups (IRS). In the radiation + SFN groups, starting from 72 h before radiation, SFN solution was intraperitoneally injected once a day until they were sacrificed. Mice in the blank control group and the radiation + no pretreatment group were simultaneously injected intraperitoneally with an equal volume of the solvent used to dissolve SFN (PBS with a final concentration of 0.1%DMSO) until they were sacrificed. They were subjected to 6Mev-ray radiation to the lower abdominal testis area (total dose 2Gy). Twenty-four hours after radiation, six mice in each group were randomly sacrificed. Seventy-two hours after radiation, the remaining mice were sacrificed.Results: The results showed that the harmful effects of ionizing radiation on testes were manifested as damage to histoarchitecture, increased oxidative stress, and apoptosis, and thus impaired male fertility. SFN injections can reverse these symptoms.Conclusions: The results showed that SFN can improve the damage of mouse testis caused by irradiation. Furthermore, SFN prevents spermatogenesis dysfunction caused by ionizing radiation by activating Nrf2 and its downstream antioxidant gene