Search results for "machine learning."

DATimeS: A machine learning time series GUI toolbox for gap-filling and vegetation phenology trends detection

2020

Abstract Optical remotely sensed data are typically discontinuous, with missing values due to cloud cover. Consequently, gap-filling solutions are needed for accurate crop phenology characterization. The here presented Decomposition and Analysis of Time Series software (DATimeS) expands established time series interpolation methods with a diversity of advanced machine learning fitting algorithms (e.g., Gaussian Process Regression: GPR) particularly effective for the reconstruction of multiple-seasons vegetation temporal patterns. DATimeS is freely available as a powerful image time series software that generates cloud-free composite maps and captures seasonal vegetation dynamics from regula…

Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion

2019

Assessing the performance of GIS- based machine learning models withdifferent accuracy measures for determining susceptibility togully erosionYounes Garosia, Mohsen Sheklabadia,⁎, Christian Conoscentib, Hamid Reza Pourghasemic,d, Kristof Van Ooste,faFaculty of Agriculture, Department of Soil Science, Bu Ali Sina University, Ahmadi Roshan Avenue, 6517838695 Hamedan, IranbDepartment of Earth and Sea Sciences (DISTEM), University of Palermo, Via Archirafi22, 90123 Palermo, ItalycCollege of Marine Sciences and Engineering, Nanjing Normal University, Nanjing, 210023, ChinadDepartment of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, IraneA- Fo…

Remaining useful life estimation of HMPE rope during CBOS testing through machine learning

2021

Fibre rope used in cranes for offshore deployment and recovery has significant potential to perform lifts with smaller cranes and vessels to reach depths limited by weight of steel wire rope. Current condition monitoring methods based on manual inspection and time-based and reactive maintenance have significant potential for improvement coupled with more accurate remaining useful life (RUL) prediction. Machine learning has found use as a condition monitoring approach, coupled with vast improvements in data acquisition methods. This paper details data-driven RUL prediction methods based on machine learning algorithms applied on cyclic-bend-over-sheave (CBOS) tests performed on two fibre rope…

Integrated satellite data fusion and mining for monitoring lake water quality status of the Albufera de Valencia in Spain

2015

Abstract Lake eutrophication is a critical issue in the interplay of water supply, environmental management, and ecosystem conservation. Integrated sensing, monitoring, and modeling for a holistic lake water quality assessment with respect to multiple constituents is in acute need. The aim of this paper is to develop an integrated algorithm for data fusion and mining of satellite remote sensing images to generate daily estimates of some water quality parameters of interest, such as chlorophyll a concentrations and water transparency, to be applied for the assessment of the hypertrophic Albufera de Valencia. The Albufera de Valencia is the largest freshwater lake in Spain, which can often pr…

Environmentally Friendly Fuel Usage: Economic Margin of Feasibility

2019

Abstract In the world there are two main problems concerning energy and ecology. Despite the crude oil price fluctuation, it has tended to increase. Moreover fossil fuel burning emits hazard compounds, including greenhouse gas. To solve them alternative fuels for vehicle have to be used. In due to properties, their usage impacts on the engine efficiency. The alternative fuel usage needs additional investment costs on the vehicle engines adaptation and fuel supply infrastructure. So, decisions must be based on mathematical apparatus. Three submodels were used in the suggested mathematical model: energy and economic indicator for fuels; energy and economic indicator for vehicles; criteria for…

The New Era of Business Digitization through the Implementation of 5G Technology in Romania

2021

The main objective of the present research is to identify the advantages and benefits that the use and implementation of 5G technology has on the development and evolution of the Romanian business environment. The study is based on a theoretical documentation regarding existing information in the field and a descriptive analysis of the evolution of the technology in Romania and worldwide. The research method chosen is a survey based on an opinion poll (questionnaire) to find out the availability of economic entities regarding the implementation of 5G technologies, the foreseen expectations and those realized by the business environment regarding the effects of 5G technologies on the economi…

Applications of alignment-free methods in epigenomics

2013

Epigenetic mechanisms play an important role in the regulation of cell type-specific gene activities, yet how epigenetic patterns are established and maintained remains poorly understood. Recent studies have supported a role of DNA sequences in recruitment of epigenetic regulators. Alignment-free methods have been applied to identify distinct sequence features that are associated with epigenetic patterns and to predict epigenomic profiles. Here, we review recent advances in such applications, including the methods to map DNA sequence to feature space, sequence comparison and prediction models. Computational studies using these methods have provided important insights into the epigenetic reg…

Agent's actions as a classification criteria for the state space in a learning from rewards system

2008

We focus in this paper on the problem of learning an autonomous agent's policy when the state space is very large and the set of actions available is comparatively short. To this end, we use a non-parametric decision rule (concretely, a nearest-neighbour strategy) in order to cluster the state space by means of the action that leads to a successful situation. Using an exploration strategy to avoid greedy behaviour, the agent builds clusters of positively-classified states through trial and error learning. In this paper, we implement a 3D synthetic agent which plays an 'avoid the asteroid' game that suits our assumptions. Using as the state space a feature vector space extracted from a visua…

On the role of procrastination for machine learning

1992

Back-Propagation Artificial Neural Network for ERP Adoption Cost Estimation

2011

Published version of a chapter in the book: Enterprise information systems, vol 220, part 2, 180-187. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-24355-4_19 Small and medium size enterprises (SMEs) are greatly affected by cost escalations and overruns Reliable cost factors estimation and management is a key for the success of Enterprise Resource Planning (ERP) systems adoptions in enterprises generally and SMEs specifically. This research area is still immature and needs a considerable amount of research to seek solid and realistic cost factors estimation. Majority of research in this area targets the enhancement of estimates calculated by COCOMO family models.…