Titlebook: Intelligent and Fuzzy Systems; Digital Acceleration Cengiz Kahraman,A. Cagri Tolga,Irem Ucal Sari Conference proceedings 2022 The Editor(s)

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Ibrahim Yazici,Emre Ariity of criminological research conducted in the United States has increased enormously, but adequate knowledge about crime causation has not increased proportionately. Particularly prior to the last quarter of the nineteenth century, most men who advanced theories about crime causation did so in an

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Mert Candar,Alp Üstündağh of the theory’s popularity probably has arisen from its negative implications, namely that criminality and delinquency are not biological, psychological or climatic phenomenon. Similarly, many of the criticisms reported in Chapter V seem to be addressed more to this negative implication than towar

宽度

Meltem Sanisoğlu,Tolga Kaya,Şebnem Burnazh of the theory’s popularity probably has arisen from its negative implications, namely that criminality and delinquency are not biological, psychological or climatic phenomenon. Similarly, many of the criticisms reported in Chapter V seem to be addressed more to this negative implication than towar

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Altan Cakir,Emre Ozkaya,Fatih Akkus,Ezgi Kucukbas,Okan Yilmazm arrest to adjudication to out-of-home placement to detenti.Traditionally, delinquent girls were considered an anomaly, a rare phenomenon attracting little scholarly notice. Today, more than one in four youth offenders is female, and researchers and practitioners alike are quickly turning their att

SUE

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Conference proceedings 2022ieties, etc. settle following a crisis bringing us to a new environment. Digital transformation and the new normal-appearing in many areas such as digital economy, digital finance, digital government, digital health, and digital education are the main scope of this book. The readers can benefit from

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Prediction of Gross Movie Revenue in the Turkish Box Office Using Machine Learning Techniquesdge regression and the lasso, tree-based methods including random forest and boosting, SVM and KNN regression. All models were built using the R programming language. Methods were compared using their MSE values. The lowest MSE was obtained with the Random Forest model.

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An Improved Animal Migration Optimization Approach for Extreme Learning Machine Tuninguggested algorithm was tested on 7 well-recognized classification benchmarking datasets and compared with the basic animal migration optimization metaheuristics and other techniques developed thus far. According to experimental findings, proposed approach obtains improved generalization performance

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Store-based Demand Forecasting of a Company via Ensemble Learningle learning algorithms and traditional machine learning algorithms were compared. To improve the results obtained, hyperparameter optimization was applied to the most successful algorithms and increased prediction success.