Search results for "Predictive analytics"
showing 9 items of 9 documents
System Dynamics in the Predictive Analytics of Container Freight Rates
2021
This study proposes a two-tier cross-validation and backtesting procedure, including expanding and rolling-window test metrics in predictive analytics of container freight rates by utilizing the system dynamics approach. The study utilized system dynamics to represent the nonlinear complex structure of container freight rates for predictive analytics and performed univariate and multivariate time-series analysis as benchmarks of the conventional approach. In particular, the China containerized freight index (CCFI) has been investigated through various parametric methodologies (both conventional time-series and system dynamics approaches). This study follows a strict validation process cons…
Development and external validation of a clinical prediction model for functional impairment after intracranial tumor surgery
2021
OBJECTIVE Decision-making for intracranial tumor surgery requires balancing the oncological benefit against the risk for resection-related impairment. Risk estimates are commonly based on subjective experience and generalized numbers from the literature, but even experienced surgeons overestimate functional outcome after surgery. Today, there is no reliable and objective way to preoperatively predict an individual patient’s risk of experiencing any functional impairment. METHODS The authors developed a prediction model for functional impairment at 3 to 6 months after microsurgical resection, defined as a decrease in Karnofsky Performance Status of ≥ 10 points. Two prospective registries in…
Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)
2017
International audience; This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the pred…
Leveraging BIM and Big Data to deliver well maintained highways
2017
The Highway infrastructure is one of the most valuable assets for any state or national Government. Efficient operations of Highways lead to success of national and local economies as well as improve the quality of life of the general public dependent on it. In order to ensure aging road networks continues to move with its ever increasing number of users, requires maintenance and improvements to the road network at the highest standard. Increasing scrutiny over the cost of maintenance along with increasing pressure from Government and the public for transparency over road network spending, has made a strong case for more efficient management of the Highway road asset and traffic management…
A Virtual Milling Machine Model to Generate Machine-Monitoring Data for Predictive Analytics
2015
Real data from manufacturing processes are essential to create useful insights for decision-making. However, acquiring real manufacturing data can be expensive and time consuming. To address this issue, we implement a virtual milling machine model to generate machine monitoring data from process plans. MTConnect is used to report the monitoring data. This paper presents (1) the characteristics and specification of milling machine tools, (2) the architecture for implementing the virtual milling machine model, and (3) the integration with a simulation environment for extending to a virtual shop floor model. This paper also includes a case study to explain how to use the virtual milling machin…
Statistical learning and multiple linear regression model for network selection using MIH
2014
Award of Appreciation; International audience; A key requirement to provide seamless mobility and guaranteeing Quality of Service in heterogeneous environment is to select the best destination network during handover. In this paper, we propose a new schema for network selection based on Multiple Linear Regression Model (MLRM). A horough investigation, on a huge live data collected from GPRS/UMTS networks led to identify the Key Performance Indicators (KPIs) that play the most important role in the handover process. These KPIs are: Received Signal Code Power (RSCP), received energy per chip (Ec/No) and Available Bandwidth (ABW) of the destination network. To extract a handover model from col…
Integrated Tool for Assisted Predictive Analytics
2021
Organizations use predictive analysis in CRM (customer relationship management) applications for marketing campaigns, sales, and customer services, in manufacturing to predict the location and rate of machine failures, in financial services to forecast financial market trends, predict the impact of new policies, laws and regulations on businesses and markets, etc. Predictive analytics is a business process which consists of collecting the data, developing accurate predictive model and making the analytics available to the business users through a data visualization application. The reliability of a business process can be increased by modeling the process and formally verifying its correctn…
HSDPA Link Adaptation Improvement Based on Node-B CQI Processing
2007
In this paper HSDPA link adaptation (LA) based on Channel Quality Indicator (CQI) reports is optimised. A pre-processing of the last received CQI reports is done before the execution of the LA algorithm in the Node-B in order to obtain more profitable channel quality estimations and hence improve the LA performance. Different types of processing techniques are presented and assessed, considering from the simplest sample averaging to some more elaborated predictive algorithms. Results demonstrate that a non negligible enhancement in the LA performance can be obtained if medium and high speed users are considered.
Dataset related to article "Development and external validation of a clinical prediction model for functional impairment after intracranial tumor sur…
2021
Anonymised clinical database containing information (Age, sex, prior surgery, tumor histology and maximum diameter, expected major brain vessel or cranial nerve manipulation, resection in eloquent areas and the posterior fossa, and surgical approach were recorded) about patients of Fondazione IRCCS Istituto Besta analysed for the article “Development and external validation of a clinical prediction model for functional impairment after intracranial tumor surgery”