Stock intelligent investment strategy based on support vector machine parameter optimization algorithm

Li, Xuetao; Sun, Yi

doi:10.1007/s00521-019-04566-2

Cited by 178 publications

(60 citation statements)

References 4 publications

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“…e more they extend downward, the lower the comprehensive ability of personnel. It is a middle school and high school culture, however, with the extension of the grid level, the problems encountered by the grid specialists at the grassroots level are often more speci c, trickier, and more responsible [21]. If one does not increase professional training for this supervision group, one will only rely on intuition.…”

Section: E Level Of Specialization Of Grassroots Grid Sta Ismentioning

confidence: 99%

Grid Supervision Path of Platform Food Safety Collaborative Governance Based on Big Data

Zhang

Tian

2022

International Transactions on Electrical Energy Systems

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Food safety is the focus of people’s attention. This year, there have a lot of bad pieces of news related to food safety, which has increased people’s attention to it. According to the requirements for traceability of platform food information attributes, the article aims to study the implementation of grids for food safety governance in the context of big data. This paper designs a nonconformity rate evaluation index to screen qualified food through the grid management of the area using big data processing under the DHRA copy management strategy to achieve the function of assisting food safety supervision. The experimental results of this paper show that grid management can effectively and quickly manage food safety problems. The method of this paper can also optimize the error of food detection, and the error can reach less than 2% in the end. It makes people’s lives safer and ensures that the food they consume is safer.

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Section: E Level Of Specialization Of Grassroots Grid Sta Ismentioning

confidence: 99%

Grid Supervision Path of Platform Food Safety Collaborative Governance Based on Big Data

Zhang

Tian

2022

International Transactions on Electrical Energy Systems

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“…Li and colleagues take an SVM model as the main framework and establish a prediction model combining kernel parameters and parameter optimization. Genetic algorithm, network search, and particle swarm optimization (PSO) are used to optimize the model parameters, which enhances the applicability of the model in practice [ 6 ]. Jiang and colleagues proposed an optimized data mining algorithm based on neural network and particle swarm optimization algorithm.…”

Section: Introductionmentioning

confidence: 99%

Machine Vision and Intelligent Algorithm Based on Neural Network

Sun

2022

Computational Intelligence and Neuroscience

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Neural network algorithms and intelligent algorithms are hot topics in the field of deep learning. In this study, the neural network algorithm and intelligence are optimized, and it is used in simulation experiments to improve the target image recognition ability of the algorithm in the machine vision environment. First, this paper introduces the application of neural networks in the field of machine vision. Second, in the experiment, the improved VGG-16 convolutional neural network (CNN) model is applied to metal block defect detection. Experimental results show that the optimized network can classify metal block defects with the maximum accuracy of 99.28%. Then, the intelligent algorithm based on neural network is studied, and the CIFAR-10 data set is taken as the experimental target for training test and verification test. Using BP algorithm, particle swarm optimization algorithm (PSO-BP), and improved neural network algorithm, respectively, the convergence speed of ICS algorithm based on BP neural network is compared. In contrast, ICS-BP algorithm has the fastest convergence speed and converges when the number of iterations is 32, followed by PSO-BP algorithm.

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“…A comparative analysis between SVM and Adaptive Neuro Fuzzy Inference System (ANFIS) in terms of finger-vein identification is portrayed and the SVM is concluded as a superior technique over ANFIS with less computational time and robust classifier [ 19 ]. Further, the efficacy of SVM to forecast stock market price is improved by integrating piecewise linear representation with weighted SVM and optimized SVM techniques in [ 20 ] and [ 21 ] respectively. Long short-term memory (LSTM) is validated over ANN and SVM to predict stock index [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Effective forecasting of stock market price by using extreme learning machine optimized by PSO-based group oriented crow search algorithm

Das

Sahu

Janghel

et al. 2021

Neural Comput & Applic

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Stock index price forecasting is the influential indicator for investors and financial investigators by which decision making capability to achieve maximum benefit with minimum risk can be improved. So, a robust engine with capability to administer useful information is desired to achieve the success. The forecasting effectiveness of stock market is improved in this paper by integrating a modified crow search algorithm (CSA) and extreme learning machine (ELM). The effectiveness of proposed modified CSA entitled as Particle Swarm Optimization (PSO)-based Group oriented CSA (PGCSA) to outperform other existing algorithms is observed by solving 12 benchmark problems. PGCSA algorithm is used to achieve relevant weights and biases of ELM to improve the effectiveness of conventional ELM. The impact of hybrid PGCSA ELM model to predict next day closing price of seven different stock indices is observed by using performance measures, technical indicators and hypothesis test (paired t -test). The seven stock indices are considered by incorporating data during COVID-19 outbreak. This model is tested by comparing with existing techniques proposed in published works. The simulation results provide that PGCSA ELM model can be considered as a suitable tool to predict next day closing price.

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Stock intelligent investment strategy based on support vector machine parameter optimization algorithm

Cited by 178 publications

References 4 publications

Grid Supervision Path of Platform Food Safety Collaborative Governance Based on Big Data

Grid Supervision Path of Platform Food Safety Collaborative Governance Based on Big Data

Machine Vision and Intelligent Algorithm Based on Neural Network

Effective forecasting of stock market price by using extreme learning machine optimized by PSO-based group oriented crow search algorithm

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