A Novel Cultural Crowd Model Toward Cognitive Artificial Intelligence

Baothman, Fatmah; Abulnaja, Osama Ahmed; Muhdher, Fatima Jafar

doi:10.32604/cmc.2021.017637

Cited by 1 publication

(30 citation statements)

References 37 publications

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“…Our objective was to enhance Crowd Management (CM) by improving crowd collectivity, density, flow rate, and satisfaction. In doing so, we recognized the most impactful HCD in concern with the prediction of crowds' social and physical behavior [1]. In addition, we discovered that individual cultural features could positively or negatively affect crowd behavior.…”

Section: Introductionmentioning

confidence: 93%

“…In earlier work, we constructed the Cultural Crowd-Artificial Neural Network (CC-ANN), which is a sophisticated learning model that utilizes the Hofstede Cultural Dimensions (HCDs) of crowds to predict their physical behavior (speed and distance) as well as their social behavior (cohesion and collectivity) [1]. The CC-ANN is predictive analytics supervised learning model.…”

Section: Introductionmentioning

confidence: 99%

“…The six HCDs that were utilized in our previous study were "Power Distance (PDI), Individualism (IDV), Masculinity (MAS), Uncertainty Avoidance (UAI), Long-Term Orientation (LTO), and Indulgence (IVR)" [1]. The research focused on groups of individuals within a crowd by using the Cultural Crowds (CC) learning model, which was designed to elicit relationships between a crowd's cultural, social, and physical characteristics via an Artificial Neural Network (ANN) [1]. Our objective was to enhance Crowd Management (CM) by improving crowd collectivity, density, flow rate, and satisfaction.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the CC-ANN could be integrated into decision-making tools for cognitive CM systems, such as the prediction of crowd behavior before large groups arrive at an event site to avoid overcrowding or the production of backup plans in unforeseen circumstances. Furthermore, information can be gathered automatically by cognitive system agents supported by Internet of Things technologies and sensors [1].…”

Section: Introductionmentioning

confidence: 99%

“…Based on our previous work [1], the researchers suggested that additional nations and cultures should be included in a further study to gain a more comprehensive insight into the results and relationships. Therefore, this study is considered a step forward, as a new culture was added to the CC-ANN.…”

Section: Introductionmentioning

confidence: 99%

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Investigating the Cultural Impact on Predicting Crowd Behavior

2023

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The Cultural Crowd–Artificial Neural Network (CC-ANN) takes the cultural dimensions of a crowd into account, based on Hofstede Cultural Dimensions (HCDs), to predict social and physical behavior concerning cohesion, collectivity, speed, and distance. This study examines the impact of applying the CC-ANN learning model on more cultures to test the effect of predicting crowd behavior and the relationships among their characteristics. Our previous work which applied the CC-ANN only included eight nations using the six HCDs. In this paper, we including the United Arab Emirates (UAE) in the CC-ANN as a new culture which aided a comparative study with four HCDs, with and without the UAE, using Mean Squared Error (MSE) for evaluation. The results indicated that most of the best-case experiments involved the UAE having the lowest MSE: 0.127, 0.014, and 0.010, which enhanced the CC-ANN model’s ability to predict crowd behavior. Moreover, the links between the cultural, sociological, and physical properties of crowds can be seen from a broader perspective with stronger correlations using the CC-ANN in more countries with diverse cultures.

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Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%