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Article ; Online: Machine Learning and Geo-Based Multi-Criteria Decision Support Systems in Analysis of Complex Problems

Behrouz Pirouz / Aldo Pedro Ferrante / Behzad Pirouz / Patrizia Piro

ISPRS International Journal of Geo-Information, Vol 10, Iss 424, p

2021 Volume 424

Abstract: Many complex problems require a multi-criteria decision, such as the COVID-19 pandemic that affected nearly all activities in the world. In this regard, this study aims to develop a multi-criteria decision support system considering the sustainability, ... ...

Abstract	Many complex problems require a multi-criteria decision, such as the COVID-19 pandemic that affected nearly all activities in the world. In this regard, this study aims to develop a multi-criteria decision support system considering the sustainability, feasibility, and success rate of possible approaches. Therefore, two models have been developed: Geo-AHP (applying geo-based data) and BN-Geo-AHP using probabilistic techniques (Bayesian network). The ranking method of Geo-APH is generalized, and the equations are provided in a way that adding new elements and variables would be possible by experts. Then, to improve the ranking, the application of the probabilistic technique of a Bayesian network and the role of machine learning for database and weight of each parameter are explained, and the model of BN-Geo-APH has been developed. In the next step, to show the application of the developed Geo-AHP and BN-Geo-AHP models, we selected the new pandemic of COVID-19 that affected nearly all activities, and we used both models for analysis. For this purpose, we first analyzed the available data about COVID-19 and previous studies about similar virus infections, and then we ranked the main approaches and alternatives in confronting the pandemic of COVID-19. The analysis of approaches with the selected alternatives shows the first ranked approach is massive vaccination and the second ranked is massive swabs or other tests. The third is the use of medical masks and gloves, and the last ranked is the lockdown, mostly due to its major negative impact on the economy and individuals.
Keywords	machine learning ; AHP ; geo-based data ; multi-criteria ; COVID-19 ; environment ; Geography (General) ; G1-922
Subject code	006
Language	English
Publishing date	2021-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Novel Multipurpose Self-Irrigated Green Roof with Innovative Drainage Layer

Behrouz Pirouz / Stefania Anna Palermo / Gianfranco Becciu / Umberto Sanfilippo / Hana Javadi Nejad / Patrizia Piro / Michele Turco

Hydrology, Vol 10, Iss 57, p

2023 Volume 57

Abstract: Climate change is a significant problem that many countries are currently facing, and green roofs (GRs) are one of the suitable choices to confront it and decrease its impacts. The advantages of GRs are numerous, such as stormwater management, thermal ... ...

Abstract	Climate change is a significant problem that many countries are currently facing, and green roofs (GRs) are one of the suitable choices to confront it and decrease its impacts. The advantages of GRs are numerous, such as stormwater management, thermal need reduction, runoff quality, and life quality improvement. However, there are some limitations, including the weight, limits in water retention, irrigation in the drought period, suitability of harvested water for building usages, installation on sloped roofs, and high cost. Therefore, developing a novel system and design for GRs with higher efficiency and fewer negative points seems necessary and is the main scope of this research. In this regard, a novel multipurpose self-irrigated green roof with an innovative drainage layer combined with specific multilayer filters has been developed. The application of the proposed system in terms of water retention capacity, water storage volume, runoff treatment performance, irrigation system, drainage layer, application of the harvested water for domestic purposes, and some other aspects has been analyzed and compared with the conventional systems with a focus on extensive green roofs. The results demonstrate that this novel green roof would have many advantages including less weight due to the replacement of the gravel drainage layer with a pipeline network for water storage, higher water retention capacity due to the specific design, higher impacts on runoff treatment due to the existence of multilayer filters that can be changed periodically, easier installation on flat and sloped roofs, the possibility of using the collected rainfall for domestic use, and fewer irrigation water demands due to the sub-surface self-irrigation system.
Keywords	NBSs ; self-irrigation ; green roof ; sustainable development ; capillarity ; water filters ; Science ; Q
Subject code	600
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Investigating a Serious Challenge in the Sustainable Development Process

Behrouz Pirouz / Sina Shaffiee Haghshenas / Sami Shaffiee Haghshenas / Patrizia Piro

Sustainability ; Volume 12 ; Issue 6

Analysis of Confirmed cases of COVID-19 (New Type of Coronavirus) Through a Binary Classification Using Artificial Intelligence and Regression Analysis

2020

Abstract: Nowadays, sustainable development is considered a key concept and solution in creating a promising and prosperous future for human societies. Nevertheless, there are some predicted and unpredicted problems that epidemic diseases are real and complex ... ...

Abstract	Nowadays, sustainable development is considered a key concept and solution in creating a promising and prosperous future for human societies. Nevertheless, there are some predicted and unpredicted problems that epidemic diseases are real and complex problems. Hence, in this research work, a serious challenge in the sustainable development process was investigated using the classification of confirmed cases of COVID-19 (new version of Coronavirus) as one of the epidemic diseases. Hence, binary classification modeling was used by the group method of data handling (GMDH) type of neural network as one of the artificial intelligence methods. For this purpose, the Hubei province in China was selected as a case study to construct the proposed model, and some important factors, namely maximum, minimum, and average daily temperature, the density of a city, relative humidity, and wind speed, were considered as the input dataset, and the number of confirmed cases was selected as the output dataset for 30 days. The proposed binary classification model provides higher performance capacity in predicting the confirmed cases. In addition, regression analysis has been done and the trend of confirmed cases compared with the fluctuations of daily weather parameters (wind, humidity, and average temperature). The results demonstrated that the relative humidity and maximum daily temperature had the highest impact on the confirmed cases. The relative humidity in the main case study, with an average of 77.9%, affected positively, and maximum daily temperature, with an average of 15.4 ° C, affected negatively, the confirmed cases.
Keywords	sustainable development ; COVID-19 ; GMDH algorithm ; binary classification ; environmental factors ; covid19
Language	English
Publishing date	2020-03-20
Publisher	Multidisciplinary Digital Publishing Institute
Publishing country	ch
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Investigating a Serious Challenge in the Sustainable Development Process

Behrouz Pirouz / Sina Shaffiee Haghshenas / Sami Shaffiee Haghshenas / Patrizia Piro

Sustainability, Vol 12, Iss 6, p

Analysis of Confirmed cases of COVID-19 (New Type of Coronavirus) Through a Binary Classification Using Artificial Intelligence and Regression Analysis

2020 Volume 2427

Abstract	Nowadays, sustainable development is considered a key concept and solution in creating a promising and prosperous future for human societies. Nevertheless, there are some predicted and unpredicted problems that epidemic diseases are real and complex problems. Hence, in this research work, a serious challenge in the sustainable development process was investigated using the classification of confirmed cases of COVID-19 (new version of Coronavirus) as one of the epidemic diseases. Hence, binary classification modeling was used by the group method of data handling (GMDH) type of neural network as one of the artificial intelligence methods. For this purpose, the Hubei province in China was selected as a case study to construct the proposed model, and some important factors, namely maximum, minimum, and average daily temperature, the density of a city, relative humidity, and wind speed, were considered as the input dataset, and the number of confirmed cases was selected as the output dataset for 30 days. The proposed binary classification model provides higher performance capacity in predicting the confirmed cases. In addition, regression analysis has been done and the trend of confirmed cases compared with the fluctuations of daily weather parameters (wind, humidity, and average temperature). The results demonstrated that the relative humidity and maximum daily temperature had the highest impact on the confirmed cases. The relative humidity in the main case study, with an average of 77.9%, affected positively, and maximum daily temperature, with an average of 15.4 °C, affected negatively, the confirmed cases.
Keywords	sustainable development ; covid-19 ; gmdh algorithm ; binary classification ; environmental factors ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	333
Language	English
Publishing date	2020-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Role of HVAC Design and Windows on the Indoor Airflow Pattern and ACH

Behrouz Pirouz / Stefania Anna Palermo / Seyed Navid Naghib / Domenico Mazzeo / Michele Turco / Patrizia Piro

Sustainability, Vol 13, Iss 7931, p

2021 Volume 7931

Abstract: The purpose of heating, ventilation, and air conditioning (HVAC) systems are to create optimum thermal comfort and appropriate indoor air quality (IAQ) for occupants. Air ventilation systems can significantly affect the health risk in indoor environments, ...

Abstract	The purpose of heating, ventilation, and air conditioning (HVAC) systems are to create optimum thermal comfort and appropriate indoor air quality (IAQ) for occupants. Air ventilation systems can significantly affect the health risk in indoor environments, especially those by contaminated aerosols. Therefore, the main goal of the study is to analyze the indoor airflow patterns in the heating, ventilation, and air conditioning (HVAC) systems and the impact of outlets/windows. The other goal of this study is to simulate the trajectory of the aerosols from a human sneeze, investigate the impact of opening windows on the number of air changes per hour (ACH) and exhibit the role of dead zones with poor ventilation. The final goal is to show the application of computational fluid dynamics (CFD) simulation in improving the HVAC design, such as outlet locations or airflow rate, in addition to the placement of occupants. In this regard, an extensive literature review has been combined with the CFD method to analyze the indoor airflow patterns, ACH, and the role of windows. The airflow pattern analysis shows the critical impact of inflow/outflow and windows. The results show that the CFD model simulation could exhibit optimal placement and safer locations for the occupants to decrease the health risk. The results of the discrete phase simulation determined that the actual ACH could be different from the theoretical ACH as the short circuit and dead zones affect the ACH.
Keywords	indoor environment ; airflow ; HVAC ; ACH ; UV light ; CFD ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	690
Language	English
Publishing date	2021-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: CFD Investigation of Vehicle’s Ventilation Systems and Analysis of ACH in Typical Airplanes, Cars, and Buses

Behrouz Pirouz / Domenico Mazzeo / Stefania Anna Palermo / Seyed Navid Naghib / Michele Turco / Patrizia Piro

Sustainability, Vol 13, Iss 6799, p

2021 Volume 6799

Abstract: The simulation of the ventilation and the heating, ventilation, and air conditioning (HVAC) systems of vehicles could be used in the energy demand management of vehicles besides improving the air quality inside their cabins. Moreover, traveling by public ...

Abstract	The simulation of the ventilation and the heating, ventilation, and air conditioning (HVAC) systems of vehicles could be used in the energy demand management of vehicles besides improving the air quality inside their cabins. Moreover, traveling by public transport during a pandemic is a concerning factor, and analysis of the vehicle’s cabin environments could demonstrate how to decrease the risk and create a safer journey for passengers. Therefore, this article presents airflow analysis, air changes per hour (ACH), and respiration aerosols’ trajectory inside three vehicles, including a typical car, bus, and airplane. In this regard, three vehicles’ cabin environment boundary conditions and the HVAC systems of the selected vehicles were determined, and three-dimensional numerical simulations were performed using computational fluid dynamic (CFD) modeling. The analysis of the airflow patterns and aerosol trajectories in the selected vehicles demonstrate the critical impact of inflow, outflow, and passenger’s locations in the cabins. The CFD model results exhibited that the lowest risk could be in the airplane and the highest in the bus because of the location of airflows and outflows. The discrete CFD model analysis determined the ACH for a typical car of about 4.3, a typical bus of about 7.5, and in a typical airplane of about 8.5, which were all less than the standard protocol of infection prevention, 12 ACH. According to the results, opening windows in the cars could decrease the aerosol loads and improve the low ACH by the HVAC systems. However, for the buses, a new design for the outflow location or an increase in the number of outflows appeared necessary. In the case of airplanes, the airflow paths were suitable, and by increasing the airflow speed, the required ACH might be achieved. Finally, in the closed (recirculating) systems, the role of filters in decreasing the risk appeared critical.
Keywords	HVAC ; CFD ; car ; bus ; airplane ; airflow ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	690
Language	English
Publishing date	2021-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Development of an Assessment Method for Investigating the Impact of Climate and Urban Parameters in Confirmed Cases of COVID-19

Behrouz Pirouz / Sina Shaffiee Haghshenas / Behzad Pirouz / Sami Shaffiee Haghshenas / Patrizia Piro

International Journal of Environmental Research and Public Health, Vol 17, Iss 2801, p

A New Challenge in Sustainable Development

2020 Volume 2801

Abstract: Sustainable development has been a controversial global topic, and as a complex concept in recent years, it plays a key role in creating a favorable future for societies. Meanwhile, there are several problems in the process of implementing this approach, ...

Abstract	Sustainable development has been a controversial global topic, and as a complex concept in recent years, it plays a key role in creating a favorable future for societies. Meanwhile, there are several problems in the process of implementing this approach, like epidemic diseases. Hence, in this study, the impact of climate and urban factors on confirmed cases of COVID-19 (a new type of coronavirus) with the trend and multivariate linear regression (MLR) has been investigated to propose a more accurate prediction model. For this propose, some important climate parameters, including daily average temperature, relative humidity, and wind speed, in addition to urban parameters such as population density, were considered, and their impacts on confirmed cases of COVID-19 were analyzed. The analysis was performed for three case studies in Italy, and the application of the proposed method has been investigated. The impacts of parameters have been considered with a delay time from one to nine days to find out the most suitable combination. The result of the analysis demonstrates the effectiveness of the proposed model and the impact of climate parameters on the trend of confirmed cases. The research hypothesis approved by the MLR model and the present assessment method could be applied by considering several variables that exhibit the exact delay of them to new confirmed cases of COVID-19.
Keywords	sustainable development ; climate and urban parameters ; COVID-19 ; MLR ; Medicine ; R ; covid19
Subject code	710
Language	English
Publishing date	2020-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Development of an Assessment Method for Investigating the Impact of Climate and Urban Parameters in Confirmed Cases of COVID-19

Behrouz Pirouz / Sina Shaffiee Haghshenas / Behzad Pirouz / Sami Shaffiee Haghshenas / Patrizia Piro

International Journal of Environmental Research and Public Health ; Volume 17 ; Issue 8

A New Challenge in Sustainable Development

2020

Abstract	Sustainable development has been a controversial global topic, and as a complex concept in recent years, it plays a key role in creating a favorable future for societies. Meanwhile, there are several problems in the process of implementing this approach, like epidemic diseases. Hence, in this study, the impact of climate and urban factors on confirmed cases of COVID-19 (a new type of coronavirus) with the trend and multivariate linear regression (MLR) has been investigated to propose a more accurate prediction model. For this propose, some important climate parameters, including daily average temperature, relative humidity, and wind speed, in addition to urban parameters such as population density, were considered, and their impacts on confirmed cases of COVID-19 were analyzed. The analysis was performed for three case studies in Italy, and the application of the proposed method has been investigated. The impacts of parameters have been considered with a delay time from one to nine days to find out the most suitable combination. The result of the analysis demonstrates the effectiveness of the proposed model and the impact of climate parameters on the trend of confirmed cases. The research hypothesis approved by the MLR model and the present assessment method could be applied by considering several variables that exhibit the exact delay of them to new confirmed cases of COVID-19.
Keywords	sustainable development ; climate and urban parameters ; COVID-19 ; MLR ; covid19
Subject code	710
Language	English
Publishing date	2020-04-18
Publisher	Multidisciplinary Digital Publishing Institute
Publishing country	ch
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Role of the Extensive Green Roofs on Decreasing Building Energy Consumption in the Mediterranean Climate

Mario Maiolo / Behrouz Pirouz / Roberto Bruno / Stefania Anna Palermo / Natale Arcuri / Patrizia Piro

Sustainability, Vol 12, Iss 1, p

2020 Volume 359

Abstract: Buildings portion in global energy consumption is 40%, and in the building envelope, the roof is a crucial point for improving indoor temperature, especially in the last and second last floors. Studies show that green roofs can be applied to moderate ... ...

Abstract	Buildings portion in global energy consumption is 40%, and in the building envelope, the roof is a crucial point for improving indoor temperature, especially in the last and second last floors. Studies show that green roofs can be applied to moderate roof temperature and affect the indoor temperature in summer and winter. However, the performance of green roofs depends on several parameters such as climate, irrigation, layer materials, and thickness. In this context, the present research deals with a comprehensive experimental analysis of different thermal impacts of green roofs in summer and winter in a Mediterranean climate. Measurements carried out in one year in three different types of green roofs with different thicknesses, layers, and with and without the insulation layer. The analysis determined the possible period that indoor cooling or heating might be required with and without green roofs and demonstrated the positive impact of green roofs in moderating the roof temperature and temperature fluctuations, which in summer was remarkable. In conclusion, since in the Mediterranean climate, the thermal differences between green roofs and conventional roofs in summer are much higher than winter, it seems that the green roof without an insulation layer would show better performance.
Keywords	green roof ; sustainability ; heat flux ; building energy consumption ; roof temperature ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	690
Language	English
Publishing date	2020-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Decreasing Water Footprint of Electricity and Heat by Extensive Green Roofs

Behrouz Pirouz / Stefania Anna Palermo / Mario Maiolo / Natale Arcuri / Patrizia Piro

Sustainability, Vol 12, Iss 10178, p

Case of Southern Italy

2020 Volume 10178

Abstract: Electrical and energy production have a noticeable water footprint, and buildings′ share of global energy consumption is about 40%. This study presents a comprehensive experimental analysis of different thermal impacts and water consumption of green ... ...

Abstract	Electrical and energy production have a noticeable water footprint, and buildings′ share of global energy consumption is about 40%. This study presents a comprehensive experimental analysis of different thermal impacts and water consumption of green roofs in a Mediterranean climate. The study aims to investigate the use of water directly for green roofs and reduce the water footprint of energy in summer and winter due to its thermal impacts. The measurements were carried out for an extensive green roof with an area of 55 m 2 and a thickness of 22 cm, and direct water consumption by a green roof and direct and indirect water consumption by cooling and heating systems were analyzed. According to the analysis, in summer, the maximum roof temperature on a conventional roof was 72 °C, while under the green roof it was 30.3 °C. In winter, the minimum roof temperature on a conventional roof was −8.6 °C, while under the green roof it was 7.4 °C. These results show that green roofs affect energy consumption in summer and winter, and the corresponding thermal requirements for the building have a water footprint regarding energy production. In summer, the thermal reduction in the water footprint by a green roof was 48 m 3 if an evaporative air conditioner is used and 8.9 m 3 for a compression air conditioner, whereas the water consumed in the green roof was 8.2 m 3 . Therefore, using water directly in the green roof would reduce the energy consumption in buildings, and thus less water has to be used in power plants to provide the same thermal impact. In winter, green roofs′ water consumption was higher than the thermal water footprint; however, there is no need to irrigate the green roof as the water consumed comes from precipitation. This experimental analysis determines that in the Mediterranean climate, green roofs allow the achievement of the same thermal conditions for buildings in both summer and winter, with a reduction in water consumption.
Keywords	water and energy ; green roofs ; Mediterranean climate ; water footprint ; power plant ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	690
Language	English
Publishing date	2020-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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