José Antonio Moscoso López

Universidad de Cádiz | UCA · Research Group in Intelligent Modelling of System

The aim of this work is to accomplish an in-depth analysis of the air pollution in the two main cities of the Bay of Algeciras (Spain). A large database of air pollutant concentrations and weather measurements were collected using a monitoring network installed throughout the region from the period of 2010–2015. The concentration parameters contain...

The Air Quality Index (AQI) shows the state of air pollution in a unique and more understandable way. This work aims to forecast the AQI in Algeciras (Spain) 8 hours in advance. The AQI is calculated indirectly through the predicted concentrations of five pollutants (O3, NO2, CO, SO2 and PM10) to achieve this goal. Artificial neural networks (ANNs)...

In recent decades, High-Speed Railway (HSR) lines have become one of the most extended and environmental-friendly ways to plan new mass transport networks. These systems are directly influenced by its operational speed generated dynamic effects and the areas where it runs through. This necessarily requires to predict ground-borne vibrations generat...

The aim of this study is to create an intelligent system that improves the efficiency of garbage collection, (cardboard waste, in this particular case). The number of cardboard containers to be collected each day will be determined based on a prediction made on the filled volume recorded in each container. It will be reflected in the cost and fuel...

This study presents a comparison between sixteen filter ranking methods applied to a real air pollution problem. Adaptations of the Minimum-Redundancy-Maximum-Relevance (mRMR) algorithm to use the Spearman's rank correlation, the kernel canonical correlation analysis, the Hilbert–Schmidt independence criterion, correntropy, the Pearson's correlatio...

The objective of this work is to obtain reliable predictions of SO2 concentrations in a port-city, Algeciras, located in Andalusia, the south of Spain. One of the main hypotheses to confirm consists of the influence of vessel traffic. An experimental procedure has been designed in order to check if this hypothesis could be confirmed. A database of...

The aim of this study is to obtain reliable predictions of the volume of filling cardboard containers. The number of cardboard containers to be collected each day will be determined based on a prediction made on the filled volume recorded in each container. Therefore, the efficiency of garbage collection would be improved in terms of cost and fuel...

The aim of this study is to create an intelligent system that improves the efficiency of garbage collection, (cardboard waste, in this particular case). The number of cardboard containers to be collected each day will be determined based on a prediction made on the filled volume recorded in each container. It will be reflected in the cost and fuel...

The main aim of this work was to measure the influence of the volume of shipping over the Sulphur dioxide (SO2) concentration in the air pollution in two monitoring stations located at Algeciras city and Alcornocales Park developing the same analysis in these two locations. The target is to demonstrate the assumption that Algeciras is more affected...

This study aims to produce accurate predictions of the NO2 concentrations at a specific station of a monitoring network located in the Bay of Algeciras (Spain). Artificial neural networks (ANNs) and sequence-to-sequence long short-term memory networks (LSTMs) were used to create the forecasting models. Additionally, a new prediction method was prop...

Air Quality Index (AQI) is an index to inform the daily air quality. AQI is a dimensionless quantity to show the state of air pollution simplifying the information of concentrations in \(\mu g/m^3\). Air quality indexes have been established for each of the five pollutants located in an interesting area to study in as Algeciras (Spain). Hourly data...

The main aim of this work was to measure the influence of the volume of shipping over the Sulphur dioxide (SO2) concentration in the air pollution in two monitoring stations located at Algeciras city and Alcornocales Park developing the same analysis in these two locations. The target is to demonstrate the assumption that Algeciras is more affected...

An accurate prediction of freight volume at the sanitary facilities of seaports is a key factor to improve planning operations and resource allocation. This study proposes a hybrid approach to forecast container volume at the sanitary facilities of a seaport. The methodology consists of a three-step procedure, combining the strengths of linear and...

The uncertainty cargo flow problem establishes a limitation in ports management where decision-making processes need accurate information of the future values. This work aims at predicting the future values of Ro-Ro perishable cargo flow at the Port of Algeciras Bay using a machine learning-based forecasting system. Two datasets consisting of daily...

An accurate forecast of freight demand at sanitary facilities of ports is one of the key challeng-es for transport policymakers to better allocate resources and to improve planning operations. This paper proposes a combined hybrid approach to predict the short-term volume of containers passing through the sanitary facilities of a maritime port. The...

Machine learning methods are a powerful tool to detect workload peaks and congestion in goods inspection facilities of seaports. In this paper, a time series data of freight inspection volume at the Border Inspections Posts in the Port of Algeciras Bay was used to construct 4 datasets based on different sizes of autoregressive window and several ma...

The Bay of Algeciras (Spain) is one of the most industrialized areas in Spain. Furthermore, the Port of Algeciras moved about 100 Millions of Tons in 2018. Therefore, this region could be one of the most affected territories by air pollution in Spain. An exhaustive statistical analysis of the different monitoring stations has been carried out in or...

Origin-destination (OD) matrix estimation is an important field in urban and transportation planning frameworks. This matrix gives information on the transportation made between different points of an area. This information is contained in a target OD matrix, which is a result of the data collection phase. The information comes from a sample survey...

Steel-making process is a complex procedure involving the presence of exogenous materials which could potentially lead to non-metallic inclusions. Determining the abundance of inclusions in the earliest stage possible may help to reduce costs and avoid further post-processing manufacturing steps to alleviate undesired effects. This paper presents a...

This study attempts to create an optimal forecasting model of daily Ro-Ro freight traffic at ports by using Empirical Mode Decomposition (EMD) and Permutation Entropy (PE) together with an Artificial Neural Networks (ANNs) as a learner method. EMD method decomposes the time series into several simpler subseries easier to predict. However, the numbe...

The forecasting of the freight transportation provides a helpful information in the management of ports environment and can be used as a decision-making tool. This work addresses the forecasting of ro-ro (roll-on roll-off) freight flow in a port using a two-stage approach by an ensemble of the best Support Vector Regression (SVR) models. The time s...

The Ro-Ro (Roll-on Roll-off) freight forecasting plays an important role in ports management in the logistic node of the Strait of Gibraltar. International freight trips are subject to variable schedule or calendar. The use of the prediction in seven days in advance may be helpful as a decision-making tool in ports operations. This work addresses t...

This work investigates the possible improvements that a stacked ensemble can provide to NO2 estimations in a monitoring network located in the Bay of Algeciras (Spain). In the proposed ensemble, ANNs, linear and nonlinear genetic algorithms models have been used as the individual learners in the first stage. The non-linear GA models produce better...

This study focuses on how to determine the most relevant variables in order to estimate the hourly NO2 concentrations in a monitoring network located in the Bay of Algeciras (Spain). For each station of the network, artificial neural networks and multiple linear regression have been used to compute hourly estimation models. Meteorological variables...

This study is focused on calculation of a reliable estimation of the hourly concentration value of NO₂ at a monitoring station based on a data fusion approach. Different feature selection procedures have been tested and their results were used as inputs to an artificial neural network (ANN) two-stage approach. The final aim is to develop a data fus...

This study is focused on achieving a reliable prediction of the daily number of goods subject to inspection at Border Inspections Posts (BIPs). The final aim is to develop a prediction tool in order to aid the decision-making in the inspection process. The best artificial neural network (ANN) model was obtained by applying the Bayesian regularizati...

This study is focused on calculation of a reliable estimation of the hourly concentration value of NO₂ at a monitoring station based on a data fusion approach. Different feature selection procedures have been tested and their results were used as inputs to an artificial neural network (ANN) two-stage approach. The final aim is to develop a data fus...

A high number of freight inspections carried out at Border Inspection Posts (BIPs) of ports could lead to significant time delays and congestion problems within the port system, decreasing the efficiency of the port. Therefore, this work is focused on achieving the most accurate prediction of the daily number of goods subject to inspection at BIPs....

The forecasting of the freight transportation, especially the short-term case, is an important topic in the daily supply chain management. Intermodal freight transportation is subject to multiple complex calendar effects arising in the port environment. The use of prediction methods provides information that may be helpful as a decision-making tool...

Forecasting of future intermodal traffic demand is very important for decision making in ports operations management. The use of accurate prediction tools is an issue that awakens a lot of interest among transport researchers. Intermodal freight forecasting plays an important role in ports management and in the planning of the principal port activi...

The prediction of freight congestion (cargo peaks) is an important tool for decision making and it is this paper’s main object of study. Forecasting freight flows can be a useful tool for the whole logistics chain. In this work, a complete methodology is presented in order to obtain the best model to predict freight congestion situations at ports....

The development of a reliable tool to know the behaviour of stainless steel on localized corrosion is necessary to achieve a proper selection of the material in the structures design. In order to know the behavioural pattern of stainless steel on localized corrosion, a total of 60 samples of austenitic stainless steel were subjected to polarization...

The objective of this article is to predict volumes of Ro-Ro (Roll-on, Roll-off) freight in order to apply this prediction as a decision making tool in logistics planning and port organization. This tool can help to improve supply chain performance in a Ro-Ro terminal. Seasonal ARIMA (SARIMA) and Artificial Neural Networks (ANNs) were the forecasti...