Blar i Institutt for økonomi og it på tittel
Viser treff 86-105 av 152
-
Norwegian entrepreneurs (1880-1930s) and their “new America”: a historical perspective on transnational entrepreneurship and ecosystem development in the Russian Arctic
(Peer reviewed; Journal article, 2022)Purpose: This paper aims to present a historical case study of Norwegian transnational entrepreneurs (1880s–1930s) and the ecosystems that they founded in Russia’s Arctic periphery. Drawing from the contemporary transnational ... -
A Novel Application of League Championship Optimization (LCA): Hybridizing Fuzzy Logic for Soil Compression Coefficient Analysis
(Peer reviewed; Journal article, 2020)Employing league championship optimization (LCA) technique for adjusting the membership function parameters of the adaptive neuro-fuzzy inference system (ANFIS) is the focal objective of the present study. The mentioned ... -
Novel ensembles of deep learning neural network and statistical learning for flash-flood susceptibility mapping
(Peer reviewed; Journal article, 2020)This study aimed to assess flash-flood susceptibility using a new hybridization approach of Deep Neural Network (DNN), Analytical Hierarchy Process (AHP), and Frequency Ratio (FR). A catchment area in south-eastern Romania ... -
A Novel GIS-Based Random Forest Machine Algorithm for the Spatial Prediction of Shallow Landslide Susceptibility
(Peer reviewed; Journal article, 2020)This study developed and verified a new hybrid machine learning model, named random forest machine (RFM), for the spatial prediction of shallow landslides. RFM is a hybridization of two state-of-the-art machine learning ... -
Novel Hybrid Swarm Optimized Multilayer Neural Network for Spatial Prediction of Flash Flood at Tropical Area Using Sentinel-1 SAR Imagery and Geospatial data
(Journal article; Peer reviewed, 2018)Flash floods are widely recognized as one of the most devastating natural hazards in the world, therefore prediction of flash flood-prone areas is crucial for public safety and emergency management. This research proposes ... -
Novel Nature-Inspired Hybrids of Neural Computing for Estimating Soil Shear Strength
(Peer reviewed; Journal article, 2019)This paper focuses on the prediction of soil shear strength (SSS), which is one of the most fundamental parameters in geotechnical engineering. Consisting of 12 influential factors, namely depth of sample, percentage of ... -
A novel semantic segmentation approach based on U-Net, WU-Net, and U-Net++ deep learning for predicting areas sensitive to pluvial flood at tropical area
(Peer reviewed; Journal article, 2023)Floods remain one of the most devastating weather-induced disasters worldwide, resulting in numerous fatalities each year and severely impacting socio-economic development and the environment. Therefore, the ability to ... -
On the adoption of static analysis for software security assessment–A case study of an open-source e-government project
(Peer reviewed; Journal article, 2021)Static Application Security Testing (SAST) is a popular quality assurance technique in software engineering. However, integrating SAST tools into industry-level product development for security assessment poses various ... -
On the integration of object-based models and field-based models in GIS
(Journal article; Peer reviewed, 2006)This paper proposes a common base-model for the classical object-based and field-based conceptual models in GIS. The model, which is called the PGOModel or 'Parameterized Geographic Object Model', is given a formal definition ... -
On the use of parameterization in the implementation of geometry
(Conference report, 2001)Parameterization of object-classes is an attractive approach during implementation of an object-oriented software system. This text discusses different cases of possible parameterization in the implementation of geometry ... -
One visitor too many: Assessing the degree of overtourism in established European urban destinations
(Peer reviewed; Journal article, 2020)Purpose: The purpose of this study is to provide a series of indicators to determine the limits to urban tourism growth, tourism gentrification and overtourism. The study addresses overtourism within the frame of urban ... -
Place-based entrepreneurs and their competitiveness: a relational perspective on small regional banks
(Peer reviewed; Journal article, 2020)This paper focuses on place-based entrepreneurs as regionally anchored companies that rely on regional resources to generate a sustained competitive advantage, but are increasingly challenged by a seemingly placeless and ... -
Post-failure success: sensemaking in problem representation reformulation
(Peer reviewed; Journal article, 2020)Failure is an inevitable feature of innovation, and management research promulgates the importance of learning from it. Key to excelling at an innovation‐based strategy is understanding the processes that can turn failures ... -
Potential of European universities as Marie Curie grantee hosts
(Peer reviewed; Journal article, 2020)This study investigates the potential of European universities as hosts for Marie Skłodowska-Curie Actions (MSCA) grantees. Factors explaining both the probability of a university hosting an MSCA grantee and its extent are ... -
Predicting Discharges in Sewer Pipes Using an Integrated Long Short-Term Memory and Entropy A-TOPSIS Modeling Framework
(Peer reviewed; Journal article, 2022)Predicting discharges in sewage systems play an essential role in reducing sewer overflows and impacts on the environment and public health. Choosing a suitable model to predict discharges in these systems is essential to ... -
Predicting Heating Load in Energy-Efficient Buildings Through Machine Learning Techniques
(Peer reviewed; Journal article, 2019)The heating load calculation is the first step of the iterative heating, ventilation, and air conditioning (HVAC) design procedure. In this study, we employed six machine learning techniques, namely multi-layer perceptron ... -
Predicting Slope Stability Failure through Machine Learning Paradigms
(Peer reviewed; Journal article, 2019)In this study, we employed various machine learning-based techniques in predicting factor of safety against slope failures. Different regression methods namely, multi-layer perceptron (MLP), Gaussian process regression ... -
Prediction of Pullout Behavior of Belled Piles through Various Machine Learning Modelling Techniques
(Journal article; Peer reviewed, 2019)The main goal of this study is to estimate the pullout forces by developing various modelling technique like feedforward neural network (FFNN), radial basis functions neural networks (RBNN), general regression neural network ... -
Preface
(Journal article; Peer reviewed, 2011) -
Product diversification and isomorphism: The case of ski resorts and “me-too” innovation
(Peer reviewed; Journal article, 2021)Many ski-lift operators are trying to diversify their business by opening summer parks and in so doing, to reposition their resorts as year-round destinations. Almost half of ski-lift operators in Tyrol introduced such ...