Design and Validation of a Computational Program for Analysing Mental Maps: Aram Mental Map Analyzer

Aram, Farshid; Solgi, Ebrahim; García, Ester Higueras; S., Danial Mohammadzadeh; Mosavi, Amir; Shamshirband, Shahaboddin

doi:10.3390/su11143790

Cited by 42 publications

(41 citation statements)

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Machine learning and deep learning methods have seen to tackle these shortcomings very well through their efficient computation and intelligence [24][25][26][27][28][29]. Only during the past few years, these methods have become very popular among the research communities [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning and Machine Learning in Hydrological Processes, Climate Change and Earth Systems: A Systematic Review

Ardabili¹,

Mosavi

Dehghani

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Artificial intelligence methods and application have recently shown great contribution in modeling and prediction of the hydrological processes, climate change, and earth systems. Among them, deep learning and machine learning methods mainly have reported being essential for achieving higher accuracy, robustness, efficiency, computation cost, and overall model performance. This paper presents the state of the art of machine learning and deep learning methods and applications in this realm and the current state, and future trends are discussed. The survey of the advances in machine learning and deep learning are presented through a novel classification of methods. The paper concludes that deep learning is still in the first stages of development, and the research is still progressing. On the other hand, machine learning methods are already established in the fields, and novel methods with higher performance are emerging through ensemble techniques and hybridization.

show abstract

Section: Introductionmentioning

confidence: 99%

Deep Learning and Machine Learning in Hydrological Processes, Climate Change and Earth Systems: A Systematic Review

Ardabili¹,

Mosavi

Dehghani

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…In practice, this may be the case of an incremental process, where economic activities and mobility would gradually advance around the well-connected streets [85]. Finally, it can be said that paying attention to citizens' perceptions of their living environment is very useful in making the right decisions for urban planners who want to create a sustainable society [86]. Considering what was discussed above, it seems that, by increasing citizens' daily physical activity, the probability of suffering from obesity and, subsequently, cardiovascular diseases, diabetes and hypertension will decrease remarkably and citizens' general health will improve.…”

Section: General Healthmentioning

confidence: 99%

The Role of Urban Morphology Design on Enhancing Physical Activities and Public Health

Fathi¹,

Sajadzadeh²,

Sheshkal³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Along with environmental pollutions, urban planning has been connected to public health. The research indicates that the quality of built environments plays an important role in reducing mental disorders and overall health. The structure and shape of the city are considered as one of the factors influencing happiness and health in urban communities and the type of the daily activities of citizens. The aim of this study was to promote physical activity in the main structure of the city via urban design in a way that the main form and morphology of the city can encourage citizens to move around and have physical activity within the city. Functional, physical, cultural-social, and perceptual-visual features are regarded as the most important and effective criteria in increasing physical activities in urban spaces based on literature review. The environmental quality of urban spaces and their role in the physical activities of citizens in urban spaces were assessed by using the questionnaire tool and analytical network process (ANP) of structural equation modeling. Further, the space syntax method was utilized to evaluate the role of the spatial integration of urban spaces on improving physical activities. Based on the results, the consideration of functional diversity, spatial flexibility and integration, security, and the aesthetic and visual quality of urban spaces plays an important role in improving the physical health of citizens in urban spaces. Further, more physical activities, including motivation for walking and consequently, the sense of public health and happiness, were observed in the streets having higher linkage and space syntax indexes with their surrounding texture.

show abstract

“…SPSS software was utilized, according to the statistical data obtained from the questionnaire to examine the significance of the data in three selected intersections, and also to examine the significance of the relationships between various indices with PTC [86,87]. In order to examine cognitive maps more accurately, AramMMA software was used [88]. In this program, all the cognitive maps were overlapped, and then according to the color spectrum, it determined which locations had the most point of reference ( Figure 5).…”

Section: Psychological Parametersmentioning

confidence: 99%

The Cooling Effect of Large-Scale Urban Parks on Surrounding Area Thermal Comfort

et al. 2019

Self Cite

View full text Add to dashboard Cite

This empirical study investigates large urban park cooling effects on the thermal comfort of occupants in the vicinity of the main central park, located in Madrid, Spain. Data were gathered during hot summer days, using mobile observations and a questionnaire. The results showed that the cooling effect of this urban park of 125 ha area at a distance of 150 m could reduce air temperatures by an average of 0.63 °C and 1.28 °C for distances of 380 m and 665 meters from the park. Moreover, the degree of the physiological equivalent temperature (PET) index at a distance of 150 meters from the park is on average 2 °C PET and 2.3 °C PET less compared to distances of 380 m and 665 m, respectively. Considering the distance from the park, the correlation between occupant perceived thermal comfort (PTC) and PET is inverse. That is, augmenting the distance from the park increases PET, while the extent of PTC reduces accordingly. The correlation between these two factors at the nearest and furthest distances from the park is meaningful (p-value < 0.05). The results also showed that large-scale urban parks generally play a significant part in creating a cognitive state of high-perceived thermal comfort spaces for residents.

show abstract

Design and Validation of a Computational Program for Analysing Mental Maps: Aram Mental Map Analyzer

Cited by 42 publications

References 69 publications

Deep Learning and Machine Learning in Hydrological Processes, Climate Change and Earth Systems: A Systematic Review

Deep Learning and Machine Learning in Hydrological Processes, Climate Change and Earth Systems: A Systematic Review

The Role of Urban Morphology Design on Enhancing Physical Activities and Public Health

The Cooling Effect of Large-Scale Urban Parks on Surrounding Area Thermal Comfort

Contact Info

Product

Resources

About