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Full-Text Articles in Physical Sciences and Mathematics
A Cutting-Plane Method For Contiguity-Constrained Spatial Aggregation, Johannes Oehrlein, Jan-Henrik Haunert
A Cutting-Plane Method For Contiguity-Constrained Spatial Aggregation, Johannes Oehrlein, Jan-Henrik Haunert
Journal of Spatial Information Science
Aggregating areas into larger regions is a common problem in spatial planning, geographic information science, and cartography. The aim can be to group administrative areal units into electoral districts or sales territories, in which case the problem is known as districting. In other cases, area aggregation is seen as a generalization or visualization task, which aims to reveal spatial patterns in geographic data. Despite these different motivations, the heart of the problem is the same: given a planar partition, one wants to aggregate several elements of this partition to regions. These often must have or exceed a particular size, be …
How To Best Apply Neural Networks In Geosciences: Towards Optimal "Averaging" In Dropout Training, Afshin Gholamy, Justin Parra, Vladik Kreinovich, Olac Fuentes, Elizabeth Y. Anthony
How To Best Apply Neural Networks In Geosciences: Towards Optimal "Averaging" In Dropout Training, Afshin Gholamy, Justin Parra, Vladik Kreinovich, Olac Fuentes, Elizabeth Y. Anthony
Departmental Technical Reports (CS)
The main objectives of geosciences is to find the current state of the Earth -- i.e., solve the corresponding inverse problems -- and to use this knowledge for predicting the future events, such as earthquakes and volcanic eruptions. In both inverse and prediction problems, often, machine learning techniques are very efficient, and at present, the most efficient machine learning technique is deep neural training. To speed up this training, the current learning algorithms use dropout techniques: they train several sub-networks on different portions of data, and then "average" the results. A natural idea is to use arithmetic mean for this …
Efficient Gate System Operations For A Multipurpose Port Using Simulation Optimization, Ketki Kulkarni, Trong Khiem Tran, Hai Wang, Hoong Chuin Lau
Efficient Gate System Operations For A Multipurpose Port Using Simulation Optimization, Ketki Kulkarni, Trong Khiem Tran, Hai Wang, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Port capacity is determined by three major infrastructural resources namely, berths, yards and gates. Theadvertised capacity is constrained by the least of the capacities of the three resources. While a lot ofattention has been paid to optimizing berth and yard capacities, not much attention has been given toanalyzing the gate capacity. The gates are a key node between the land-side and sea-side operations in anocean-to-cities value chain. The gate system under consideration, located at an important port in an Asiancity, is a multi-class parallel queuing system with non-homogeneous Poisson arrivals. It is hard to obtaina closed form analytic approach for …
Towards Food Service Sustainability In Suburban Environments By Optimally Locating Shared Anaerobic Digester Units, Rebecca Loraamm, Joni Downs, Robert Alonso Bair, Daniel Yeh
Towards Food Service Sustainability In Suburban Environments By Optimally Locating Shared Anaerobic Digester Units, Rebecca Loraamm, Joni Downs, Robert Alonso Bair, Daniel Yeh
Suburban Sustainability
Anaerobic digestion is an effective method for reducing food waste at the consumer level. Drawbacks associated with this strategy include high construction costs for multiple digester units and limited public awareness of the method’s commercial potential. Given the large scale problem of food waste, an approach establishing community partnerships between local businesses and primary schools is offered to combat the problem of food waste. Optimizing the placement of shared digester units enabling utilization by multiple stakeholders is the suggested mitigation method. This research explores application of the p-median problem to determine the set of optimal sites for shared anaerobic digester …
Dynamic Repositioning To Reduce Lost Demand In Bike Sharing Systems, Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet
Dynamic Repositioning To Reduce Lost Demand In Bike Sharing Systems, Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Bike Sharing Systems (BSSs) are widely adopted in major cities of the world due to concerns associated with extensive private vehicle usage, namely, increased carbon emissions, traffic congestion and usage of nonrenewable resources. In a BSS, base stations are strategically placed throughout a city and each station is stocked with a pre-determined number of bikes at the beginning of the day. Customers hire the bikes from one station and return them at another station. Due to unpredictable movements of customers hiring bikes, there is either congestion (more than required) or starvation (fewer than required) of bikes at base stations. Existing …