Many-objective optimization applied to the joint problem of inventory management and restocking policy. A case study on a pharmaceutical company is presented.
A Least Squares Support Vector Machine (LS-SVM) algorithm was developed to predict the air chamber pressure and compare it to the real signal. Regressive linear algorithms were executed for reference. The experimental data was obtained at the Mutriku wave power plant in the Basque Country, Spain.
The problem of scheduling uninterruptible shiftable devices is addressed from a multiagent perspective considering two different approaches. On one hand, a centralized architecture assumes that a single agent has the capacity to solve all agents problems. On the other, a new partially decentralized architecture is proposed to solve the same problem by distributing decision-making among agents using an heuristic algorithm with a virtual dynamic tariff as coordination mechanism.
Digital Twin of the supply chain of a pharmaceutical company, delivered as a graphical interface with data visualization and Monte Carlo simulation.
This paper contributes to industrial frameworks focused on the development of standardized system architectures for Industry 4.0, closing the gap between generic architectures and physical realizations. It proposes a platform for intelligent automation relying on a gateway or middleware between field devices, enterprise databases, and DSSs in real-time scenarios
This paper proposes a framework for intelligent automation to deal with current challenges in acquisition and management of data in industrial settings.
This work presents a novel formulation for quality control laboratory scheduling considering both equipment and analysts as constraints.
This paper proposes a prediction model based on preoperative characteristics, in order to support the decision of co-management of surgical patients in the postoperative ward setting. The model is a simple bedside decision tool that uses only four numerical variables.
This paper is a review of literature with an analysis on a selection of scientific studies for detection of non-technical losses. Non-technical losses occurring in the electric grid at level of transmission or of distribution have negative impact on economies, affecting utilities, paying consumers and states.
This paper proposes a clustering-based methodology to define the segmentation of residential gas consumers
This paper proposes a feature engineering approach and Takagi-Sugeno-based ensemble fuzzy models for predicting ICU readmissions on a daily basis.
This paper proposes the use of mixed fuzzy clustering (MFC) algorithm to simultaneously cluster time variant and time invariant data.
This paper discusses the service life prediction of natural stone claddings using a Takagi-Sugeno fuzzy model.
This paper proposes a process for the classification of new residential electricity customers. The current state of the art is extended by using a combination of smart metering and survey data and by using model-based feature selection for the classification task.
This paper proposes the use of mixed fuzzy clustering (MFC) algorithm to derive Takagi-Sugeno (TS) fuzzy models.
This paper proposes the use of probabilistic fuzzy systems (PFS) to predict mortality of septic shock patients.
The supply of steel blocks with customised dimensions for clients within the metalworking industry requires the effective management of a large and highly variable stock of steel blocks. This paper proposes a cutting decision process for daily tailored orders of a real-life steel retailer.
This paper proposes ensemble fuzzy modeling for personalized medicine in the intensive care unit (ICU), in particular for the prediction of vasopressors administration.
This paper proposes fuzzy modeling for predicting severely impaired left ventricular ejection fraction (LVEF) using patient data routinely collected in the ICU.
Intelligent Systems 4
Template by Bootstrapious. Ported to Hugo by DevCows