Mohammad Aslani

Mohammad Aslani
University of Gävle

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17
Publications
2,197
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193
Citations

Publications

Publications (17)
Conference Paper
Full-text available
Rooftop solar energy has long been regarded as a promising solution to cities’ growing energy demand and environmental problems. A reliable estimate of rooftop solar energy facilitates the deployment of photovoltaics and helps formulate renewable-related policies. This reliable estimate underpins the necessity of accurately pinpointing the areas ut...
Article
Full-text available
The considerable potential of rooftop photovoltaics (RPVs) for alleviating the high energy demand of cities has made them a proven technology in local energy networks. Identification of rooftop areas suitable for installing RPVs is of importance for energy planning. Having these suitable areas referred to as utilizable areas greatly assists in a re...
Article
Full-text available
Support vector machines (SVMs) are powerful classifiers that have high computational complexity in the training phase, which can limit their applicability to large datasets. An effective approach to address this limitation is to select a small subset of the most representative training samples such that desirable results can be obtained. In this st...
Article
Full-text available
Training support vector machines (SVMs) for pixel-based feature extraction purposes from aerial images requires selecting representative pixels (instances) as a training dataset. In this research, locality-sensitive hashing (LSH) is adopted for developing a new instance selection method which is referred to as DR.LSH. The intuition of DR.LSH rests...
Article
Traffic signal control plays a pivotal role in reducing traffic congestion. Traffic signals cannot be adequately controlled with conventional methods due to the high variations and complexity in traffic environments. In recent years, reinforcement learning (RL) has shown great potential for traffic signal control because of its high adaptability, f...
Article
Traffic signal control can be naturally regarded as a reinforcement learning problem. Unfortunately, it is one of the most difficult classes of reinforcement learning problems owing to its large state space. A straightforward approach to address this challenge is to control traffic signals based on continuous reinforcement learning. Although they h...
Article
Designing efficient traffic signal controllers has always been an important concern in traffic engineering. This is owing to the complex and uncertain nature of traffic environments. Within such a context, reinforcement learning has been one of the most successful methods owing to its adaptability and its online learning ability. Reinforcement lear...
Article
The transportation demand is rapidly growing in metropolises, resulting in chronic traffic congestions in dense downtown areas. Adaptive traffic signal control as the principle part of intelligent transportation systems has a primary role to effectively reduce traffic congestion by making a real-time adaptation in response to the changing traffic n...
Article
The daily increase of a number of vehicles in big cities poses a serious challenge to efficient traffic control. The suitable approach for optimum traffic control should be adaptive in order to successfully content with the urban traffic that has the dynamic and complex nature. Within such a context, the major focus of this research is developing a...
Article
The Multi-agent systems has shown their usefulness as an efficient approach for modeling, analyzing as well as implementing complex, dynamic and distributed applications such as robotic teams, distributed control, resource management, traffic control, land use planning, crisis management, forest fire control and to name but a few. The main challeng...
Article
Landslides are natural disasters that can cause extensive damage to both property and life every year, and therefore, generating landslide susceptibility map is essential for planning future developmental activities. The objective of this paper is to analyze the relationship between landslide locations and landslide related factors by applying regr...
Article
Weighting and integrating spatial information are vitally important in any analysis of the geospatial information systems (GIS). There are numerous sources of uncertainty in spatial phenomenon. Therefore, uncertainty in weighting spatial information must be considered. The purpose of this research is to construct a fuzzy knowledge base, which conta...
Conference Paper
Mineral potential mapping which depicts the favorability of mineralization occurring over a specified area is an important process for mineral deposit exploration. Geospatial Information Systems (GIS) can be effectively used to facilitate the mine exploration process. Moreover, there are different resources for uncertainty in spatial information an...
Article
These days one of the main concerns of transportation managers is inter-city communications. In this regard, supplying the required fuel for vehicles and consequently, suitable site location for fuel stations is considered a main issue. The location of fuel stations could influence human life tremendously, and even minor biases in selecting the loc...
Article
Spatial data in Geographic Information Systems (GIS) are inherently uncertain; and therefore a system that can handle and infer from such uncertain data is of vital importance. Fuzzy Inference System (FIS) is one of the well-known inference systems that have been considered by many scientists in the recent decades. The objective of this paper is to...
Article
Landslides are natural disasters that can damage human lives and various properties annually. Unplanned development expansions of cities results in locating inhabited area with high risk of landslides. Consequently, it is essential to generate landslide susceptibility maps for city expansions. The objective of this paper is to propose a method for...

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