Institutt for økonomi og it: Recent submissions
Now showing items 101-120 of 161
-
An Empirical Investigation on Software Practices in Growth Phase Startups.
(Chapter, 2020)Context: Software startups are software-intensive early-stage companies with high growth rates. We notice little evidence in the literature concerning engineering practices when startups transition to the growth phase. Aim: ... -
Spatial Landslide Susceptibility Assessment Based on Novel Neural-Metaheuristic Geographic Information System Based Ensembles
(Peer reviewed; Journal article, 2019)Regular optimization techniques have been widely used in landslide-related problems. This paper outlines two novel optimizations of artificial neural network (ANN) using grey wolf optimization (GWO) and biogeography-based ... -
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 ... -
Exploring the intersection between software industry and Software Engineering education - A systematic mapping of Software Engineering Trends
(Peer reviewed; Journal article, 2020)Context: Software has become ubiquitous in every corner of modern societies. During the last five decades, software engineering has also changed significantly to advance the development of various types and scales of ... -
Achieving agility and quality in product development -an empirical study of hardware startups
(Peer reviewed; Journal article, 2020)Context: Startups aim at scaling their business, often by developing innovative products with limited hu- man and financial resources. The development of software products in the startup context is known as opportunistic, ... -
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 ... -
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 ... -
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 ... -
The Kyrgyz horse: enactments and agencies in and beyond a tourism context
(Peer reviewed; Journal article, 2019)The horse has a strong cultural and historical importance in Kyrgyzstan. With a mountainous topography, the rural areas of this Central Asian country are best accessed by horse. Among all the tourism experiences Kyrgyzstan ... -
Spatial Modeling of Snow Avalanche Using Machine Learning Models and Geo-Environmental Factors: Comparison of Effectiveness in Two Mountain Regions
(Peer reviewed; Journal article, 2019)Although snow avalanches are among the most destructive natural disasters, and result in losses of life and economic damages in mountainous regions, far too little attention has been paid to the prediction of the snow ... -
Återbruk av det industriella kulturarvet i kulturarvsindustrin. Ett landsbygdsperspektiv.
(Peer reviewed; Journal article, 2019)This paper aims to examine adaptive reuse of the industrial heritage in the Swedish countryside from the point of view of four different values within the heritage process: experiential values, economic values, symbolic ... -
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 ... -
Development of Two Novel Hybrid Prediction Models Estimating Ultimate Bearing Capacity of the Shallow Circular Footing
(Peer reviewed; Journal article, 2019)In the present work, we employed artificial neural network (ANN) that is optimized with two hybrid models, namely imperialist competition algorithm (ICA) as well as particle swarm optimization (PSO) in the case of the ... -
Hybrid Machine Learning Approaches for Landslide Susceptibility Modeling
(Peer reviewed; Journal article, 2019)This paper presents novel hybrid machine learning models, namely Adaptive Neuro Fuzzy Inference System optimized by Particle Swarm Optimization (PSOANFIS), Artificial Neural Networks optimized by Particle Swarm Optimization ... -
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 ... -
Development of a Novel Hybrid Intelligence Approach for Landslide Spatial Prediction
(Peer reviewed; Journal article, 2019)We proposed an innovative hybrid intelligent approach, namely, the multiboost based naïve bayes trees (MBNBT) method for the spatial prediction of landslides in the Mu Cang Chai District of Yen Bai Province, Vietnam. The ... -
Two novel neural-evolutionary predictivetechniques of dragonfly algorithm (DA) andbiogeography-based optimization (BBO)forlandslide susceptibility analysis
(Peer reviewed; Journal article, 2019)Due to the wide application of evolutionary science in different engineering problems, the main aim of this paper is to present two novel optimizations of multi-layer perceptron (MLP) neural network, namely dragonfly ... -
Spotted Hyena Optimizer and Ant Lion Optimization in Predicting the Shear Strength of Soil
(Peer reviewed; Journal article, 2019)Two novel hybrid predictors are suggested as the combination of artificial neural network (ANN), coupled with spotted hyena optimizer (SHO) and ant lion optimization (ALO) metaheuristic techniques, to simulate soil shear ... -
Wildfire Probability Mapping: Bivariate vs. Multivariate Statistics
(Peer reviewed; Journal article, 2019)Wildfires are one of the most common natural hazards worldwide. Here, we compared the capability of bivariate and multivariate models for the prediction of spatially explicit wildfire probability across a fire-prone landscape ... -
Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM
(Peer reviewed; Journal article, 2019)Landslides are typically triggered by earthquakes or rainfall occasionally a rainfall event followed by an earthquake or vice versa. Yet, most of the works presented in the past decade have been largely focused at the ...