Diana Manjarres

Tecnalia Corporación Tecnológica

The steel industry is a key driver of new developments in the refractory industry due to its high market share (>70%) and the harsh conditions involved in the steelmaking processes. In addition, the annual refractory consumption in a special steel plant that produces more than 750.000 ton of steel per year, can reach around 10.000 ton. The RFCS Eur...

In the era of technological advances and Industry 4.0, massive data collection and analysis is a common approach followed by many industries and companies worldwide. One of the most important uses of data mining and Machine Learning techniques is to predict possible breaks or failures in industrial processes or machinery. This research designs and...

Normalisation is a preprocessing technique widely employed in Machine Learning (ML)-based solutions for industry to equalise the features’ contribution. However, few researchers have analysed the normalisation effect and its implications on the ML algorithm performance, especially on Euclidean distance-based algorithms, such as the well-known K-Nea...

Leaf wetness often emerges as the result of the exchange of atmospheric water-soluble gases between the Earth surface and the atmosphere. The importance of this feature resides in the relationship that exists between leaf wetness and various plant diseases. In order to measure this variable, there is a need for deploying physical sensors to capture...

Artificial Neural Networks (ANNs) are weighted directed graphs of interconnected neurons widely employed to model complex problems. However, the selection of the optimal ANN architecture and its parameters training is not enough to obtain reliable models. The data preprocessing stage is fundamental to improve the model’s performance. Specifically,...

Refineries are complex industrial systems that transform crude oil into more valuable subproducts. Due to the advances in sensors, easily measurable variables are continuously monitored and several data-driven soft-sensors are proposed to control the distillation process and the quality of the resultant subproducts. However, data preprocessing and...

In the last decades, a wide portfolio of Feature Weighting (FW) methods have been proposed in the literature. Their main potential is the capability to transform the features in order to contribute to the Machine Learning (ML) algorithm metric proportionally to their estimated relevance for inferring the output pattern. Nevertheless, the extensive...

Petroleum oil refineries are complex systems that convert crude into subproducts of value. The profit of the refinery depends on the quality of the resultant subproducts, which are usually determined by a laboratory analysis called “Needle penetration”. Normally, this laboratory analysis is costly and time-consuming since entails around four hours...

Clustering methods have become popular in the last years due to the need of analyzing the high amount of collected data from different fields of knowledge. Nevertheless, the main drawback of clustering is the selection of the optimal method along with its internal parameters in an unsupervised environment. In the present paper, a novel heuristic ap...

Normalization methods are widely employed for transforming the variables or features of a given dataset. In this paper three classical feature normalization methods, Standardization (St), Min-Max (MM) and Median Absolute Deviation (MAD), are studied in different synthetic datasets from UCI repository. An exhaustive analysis of the transformed featu...

Designing energy retrofitting actions poses an elevated number of problems, as the definition of the baseline, selection of indicators to measure performance, modelling, setting objectives, etc. This is time-consuming and it can result in a number of inaccuracies, leading to inadequate decisions. While these problems are present at building level,...

Energy efficiency and environmental performance optimization at the district level are following an upward trend mostly triggered by minimizing the Global Warming Potential (GWP) to 20% by 2020 and 40% by 2030 settled by the European Union (EU) compared with 1990 levels. This paper advances over the state of the art by proposing two novel multi-obj...

This paper presents a preliminary metaheuristic approach for underwater swarm robotic parameter configuration applied to optimal plume detection under time-variant scenarios. In this work the plume scanning has followed a collaborative approach that has been modelled following a real-based scenario obtained within the European project SWARMs (“Smar...

Thermal cracking is one of the most energy-consuming process in the chemical industry and its optimization has become a real challenge for the research community. In this context, this paper proposes two metaheuristic approaches based on the Genetic Algorithm (GA) and the Harmony Search (HS) algorithms for minimizing the sum of the Energy Consumpti...

Solar energy forecasting represents a key issue in order to efficiently manage the supply-demand balance and promote an effective renewable energy integration. In this regard, an accurate solar energy forecast is of utmoss importance for avoiding large voltage variations into the electricity network and providing the system with mechanisms for mana...

Heating ventilation and air conditioning (HVAC) systems represent an important amount of the total energy use in office buildings, accounting for near 30%. Moreover, in countries affected by extreme climates HVAC systems’ contribution to energy demand increases up to 50%. Therefore, the automation of energy efficient strategies that act on the Buil...

In the last years, default prediction systems have become an important tool for a wide variety of financial institutions, such as banking systems or credit business, for which being able of detecting credit and default risks, translates to a better financial status. Nevertheless, small and medium-sized enterprises did not focus its attention on cus...

Robotics deployed in the underwater medium are subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this context the so-called cost of a mission must be considered as an additional criterion when designing optimal task schedules wit...

Nowadays municipalities are facing an increasing commitment regarding the energy and environmental performance of cities and districts. The multiple factors that characterize a district scenario, such as: refurbishment strategies’ selection, combination of passive, active and control measures, the surface to be refurbished and the generation system...

The problem of partitioning a data set into disjoint groups or clusters of related items plays a key role in data analytics, in particular when the information retrieval becomes crucial for further data analysis. In this context, clustering approaches aim at obtaining a good partition of the data based on multiple criteria. One of the most challeng...

We report a critical assessment of the use of an Inverse Design (ID) approach steamed by an improved Harmony Search (IHS) algorithm for enhancing light coupling to densely integrated photonic integratic circuits (PICs) using novel grating structures. Grating couplers, performing as a very attractive vertical coupling scheme for standard silicon nan...

The objective of OptEEmAL is to develop an Optimised Energy Efficient Design Platform for refurbishment at district level. The platform will deliver an optimised, integrated and systematic design based on an Integrated Project Delivery (IPD) approach for building and district retrofitting projects. This will be achieved through the development of a...

During the last years wind energy has experimented a significant growth in comparison with other types of renewable energy sources. Accordingly, the number of wind farms has increased sharply to become one of the most developed worldwide infrastructures. Unfortunately, the high number of constraints and restrictions that must be considered nowadays...

In this paper, we propose the optimization of the parameters of a hybrid antenna for wireless applications by using a multi‐objective evolutionary programming (EP). Specifically, the antenna proposed is formed by a planar inverted‐F antenna and a coplanar patch, in the same structure. The objective functions to carry out the optimization process ar...

This paper thoroughly reviews and analyzes the main characteristics and application portfolio of the so-called Harmony Search algorithm, a meta-heuristic approach that has been shown to achieve excellent results in a wide range of optimization problems. As evidenced by a number of studies, this algorithm features several innovative aspects in its o...

The use of intelligent optimization systems has been a major topic of research in the last few years for improving the existing urban infrastructure, the traffic optimization and the mobility of citizens. These techniques are of great importance in the analysis and optimization of transportation networks, as well as their re-organization to improve...

This paper proposes the application of a novel meta-heuristic algorithm to the metropolitan wireless local area network deployment problem. In this problem, the coverage level of the deployed network must be maximized while meeting an assigned maximum budget, set beforehand. Specifically, we propose an approach based on the Harmony Search (HS) algo...

This paper presents a novel heuristic multi-criteria tool capable of generating open-access wireless network deployments by exploiting the existing broadband infrastructure. Specifically, an external user dynamically selects, by virtue of our proposed scheme, a certain network layout depending on the target percentage of non-covered users and cost...

In this paper we outline a novel global heuristic tool to deal with a combination of the Capacitated P-Median (CPMP) and the Capacitated Minimum Spanning Tree (CMST) problems. This preliminary approach provides an efficient (in terms of power consumption due to emission or signal interferences) traffic-flow design for a setup consisting of a number...

The availability of accurate location information of constituent nodes becomes essential in many applications of wireless sensor networks. In this context, we focus on anchor-based networks where the position of some few nodes are assumed to be fixed and known a priori, whereas the location of all other nodes is to be estimated based on noisy pairw...

In several wireless sensor network applications the availability of accurate nodes' location information is essential to make collected data meaningful. In this context, estimating the positions of all unknown-located nodes of the network based on noisy distance-related measurements (usually referred to as localization) generally embodies a non-con...

This paper focuses on the data fusion scenario where N nodes sense and transmit the data generated by a source S to a common destination, which estimates the original information from S more accurately than in the case of a single sensor. This work joins the upsurge of research interest in this topic by addressing the setup where the sensed informa...

In many applications based on Wireless Sensor Networks (WSNs) with static sensor nodes, the availability of accurate location information of the network nodes may become essential. The node localization problem is to estimate all the unknown node positions, based on noisy pairwise distance measurements of nodes within range of each other. Maximum L...

This paper presents a novel Grouping Harmony Search (GHS) algorithm for the Citywide Ubiquitous WiFi Network Design problem (WIFIDP). The WIFIDP is a NP-hard problem where private customers owning wireless access points connected to Internet share bandwidth with third parties. Aspects such as allocated budget and router capacities (coverage radius,...

This manuscript proposes a novel iterative approach for the so-called Switch Location Problem (SLP) based on the hybridization of a group-encoded Harmony Search combinatorial heuristic (GHS) with local search and repair methods. Our contribution over other avantgarde techniques lies on the dual application of the GHS operators over both the assignm...

One of the applications of wireless sensor networks currently undergoing active research focuses on the scenario where the information generated by a data source S is simultaneously sensed by N nodes and therefrom transmitted to a common receiver. Based on the received information from such N nodes, such receiver infers the original information fro...