Blar i Institutt for økonomi og it på tittel
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Machine-Learning-Based Classification Approaches toward Recognizing Slope Stability Failure
(Peer reviewed; Journal article, 2019)In this paper, the authors investigated the applicability of combining machine-learning-based models toward slope stability assessment. To do this, several well-known machine-learning-based methods, namely multiple linear ... -
Mapping wind erosion hazard with regression-based machine learning algorithms
(Peer reviewed; Journal article, 2020)Land susceptibility to wind erosion hazard in Isfahan province, Iran, was mapped by testing 16 advanced regression-based machine learning methods: Robust linear regression (RLR), Cforest, Non-convex penalized quantile ... -
Marine gravity anomaly mapping for the Gulf of Tonkin area (Vietnam) using Cryosat-2 and Saral/AltiKa satellite altimetry data
(Peer reviewed; Journal article, 2020)Marine gravity anomalies are essential data for determining coastal geoid, investigating tectonics and crustal structures, and offshore explorations. The objective of this study is to present a methodology for estimating ... -
Minimum Viable Products for Internet of Things Applications: Common Pitfalls and Practices
(Journal article; Peer reviewed, 2019)Internet of Things applications are not only the new opportunity for digital businesses but also a major driving force for the modification and creation of software systems in all industries and businesses. Compared to ... -
Multi-CMP system with data communication on the fly
(Journal article; Peer reviewed, 2011-02-04)The paper concerns new communication solutions for hierarchical Chip Multiprocessor (CMP) systems composed of many CMP modules interconnected by a global data exchange network. New architectural solutions for internal ... -
Neural Computing Improvement Using Four Metaheuristic Optimizers in Bearing Capacity Analysis of Footings Settled on Two-Layer Soils
(Peer reviewed; Journal article, 2019)This study outlines the applicability of four metaheuristic algorithms, namely, whale optimization algorithm (WOA), league champion optimization (LCA), moth–flame optimization (MFO), and ant colony optimization (ACO), for ... -
A New Approach Based on Balancing Composite Motion Optimization and Deep Neural Networks for Spatial Prediction of Landslides at Tropical Cyclone Areas
(Peer reviewed; Journal article, 2023)Landslides are a significant geological hazard that annually cause extensive damage and loss of life worldwide. Therefore, it is crucial to have reliable prediction models for landslide susceptibility in order to identify ... -
A New Approach of Hybrid Bee Colony Optimized Neural Computing for Estimation of Soil Compression Coefficient for Housing Construction Project
(Peer reviewed; Journal article, 2019)In the design phase of housing projects, predicting the settlement of soil layers beneath the buildings requires the estimation of the coefficient of soil compression. This study proposes a low-cost, fast, and reliable ... -
A New Hybrid Firefly–PSO Optimized Random Subspace Tree Intelligence for Torrential Rainfall-Induced Flash Flood Susceptible Mapping
(Peer reviewed; Journal article, 2020)Flash flood is one of the most dangerous natural phenomena because of its high magnitudes and sudden occurrence, resulting in huge damages for people and properties. Our work aims to propose a state-of-the-art model for ... -
A New Integrated Approach Based on the Iterative Super-Resolution Algorithm and Expectation Maximization for Face Hallucination
(Peer reviewed; Journal article, 2020)This paper proposed and verified a new integrated approach based on the iterative super-resolution algorithm and expectation-maximization for face hallucination, which is a process of converting a low-resolution face image ... -
A New Modeling Approach for Spatial Prediction of Flash Flood with Biogeography Optimized CHAID Tree Ensemble and Remote Sensing Data
(Peer reviewed; Journal article, 2020)Flash floods induced by torrential rainfalls are considered one of the most dangerous natural hazards, due to their sudden occurrence and high magnitudes, which may cause huge damage to people and properties. This study ... -
Nordic stock market performance of the travel and leisure industry during the first wave of Covid-19 pandemic
(Peer reviewed; Journal article, 2021)This article investigates the performance of the stock market and its volatility in the travel and leisure industry for three Nordic countries using daily data from June 2018 to June 2020, a period that includes the first ... -
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 ...