Application of Genetic Algorithm and Back Propagation Neural Network for Effective Personalize Web Search-Based on Clustered Query Sessions

Chawla, Suruchi

doi:10.4018/ijaec.2016010103

Cited by 8 publications

(4 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the data used is absolute numbers, the resulting series is the absolute number form of the time series. In different periods, the absolute number sequence can reflect the change process of the same phenomenon in different development periods, thereby directly reflecting the development process of the phenomenon [18]. The absolute number form of the time series is to arrange the absolute number indicators in chronological order to form a time series data sequence.…”

Section: Basic Methods Of Predicting the Sales Effect Of Football Leaguementioning

confidence: 99%

Forecast of Football League Sales Effect Based on BP Neural Network

Wei-feng

2020

Preprint

View full text Add to dashboard Cite

Football is one of the sports that is loved by people all over the world. Its sales ability in the league should not be underestimated. Moreover, football has been developed in our country since ancient times and has a huge fan base, and fans are the main target of football league sales. Predicting the sales effect of the football league is helpful for the seller to formulate a suitable sales strategy and avoid the problem of product surplus. This article mainly introduces the prediction research of football league sales effect based on BP neural network, and intends to provide ideas and methods for predicting the sales effect of football league. This paper puts forward the basic method of the sales effect prediction of the football league and the BP neural network football league sales effect prediction method to analyze and predict the sales effect of the football league. In addition, the steps of establishing BP neural network design, building BP neural network football league sales effect prediction model and applying BP neural network football league sales effect prediction model are also proposed. The experimental results of this article show that the difference between the fitting part of the neural network model and the real value of the football league sales effect sample data is in the range of , the error percentage difference is small, and the prediction results are valid。

show abstract

Section: Basic Methods Of Predicting the Sales Effect Of Football Leaguementioning

confidence: 99%

Forecast of Football League Sales Effect Based on BP Neural Network

Wei-feng

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…AI tools such as support vector machine, PNN, other types of ML are simulated and results compared when doctors are choosing the ideal highly accurate classification method for BC detection and staging (Ayer et al, n.a. ;Suruchi, 2016;Supriya and Deepa, 2020). To get the highly accurate simulation results for BC classification in this paper, the four mentioned metaheuristic algorithms are used and the results compared, which are explained in section 4 and 5.…”

Section: Breast Cancer Predictionmentioning

confidence: 99%

Using new artificial bee colony as probabilistic neural network for breast cancer data classification

Shah

2021

FEBE

View full text Add to dashboard Cite

PurposeBreast cancer is an important medical disorder, which is not a single disease but a cluster more than 200 different serious medical complications.Design/methodology/approachThe new artificial bee colony (ABC) implementation has been applied to probabilistic neural network (PNN) for training and testing purpose to classify the breast cancer data set.FindingsThe new ABC algorithm along with PNN has been successfully applied to breast cancers data set for prediction purpose with minimum iteration consuming.Originality/valueThe new implementation of ABC along PNN can be easily applied to times series problems for accurate prediction or classification.

show abstract

“…In [22] the authors introduce an approach to multilingual single-document extractive summarization where summarization is considered as an optimization or a search problem which is solved by using genetic algorithms. In [23] genetic algorithm has been applied for effective personalize web search-based on clustered query sessions. The genetic algorithm also used for term-weighting learning in term of text classification [24].…”

Section: ) Adaptive Boosting (Adaboost)mentioning

confidence: 99%

Hyper Parameter Optimization using Genetic Algorithm on Machine Learning Methods for Online News Popularity Prediction

Wicaksono¹,

Supianto²

2018

ijacsa

View full text Add to dashboard Cite

Online news is a media for people to get new information. There are a lot of online news media out there and a many people will only read news that is interesting for them. This kind of news tends to be popular and will bring profit to the media owner. That's why, it is necessary to predict whether a news is popular or not by using the prediction methods. Machine learning is one of the popular prediction methods we can use. In order to make a higher accuracy of prediction, the best hyper parameter of machine learning methods need to be determined. Determining the hyper parameter can be time consuming if we use grid search method because grid search is a method which tries all possible combination of hyper parameter. This is a problem because we need a quicker time to make a prediction of online news popularity. Hence, genetic algorithm is proposed as the alternative solution because genetic algorithm can get optimal hypermeter with reasonable time. The result of implementation shows that genetic algorithm can get the hyper parameter with almost the same result with grid search with faster computational time. The reduction in computational time is as follows: Support Vector Machine is 425.06%, Random forest is 17%, Adaptive Boosting is 651.06%, and lastly K -Nearest Neighbour is 396.72%.

show abstract

Application of Genetic Algorithm and Back Propagation Neural Network for Effective Personalize Web Search-Based on Clustered Query Sessions

Cited by 8 publications

References 67 publications

Forecast of Football League Sales Effect Based on BP Neural Network

Forecast of Football League Sales Effect Based on BP Neural Network

Using new artificial bee colony as probabilistic neural network for breast cancer data classification

Hyper Parameter Optimization using Genetic Algorithm on Machine Learning Methods for Online News Popularity Prediction

Contact Info

Product

Resources

About