On the interpretability of fuzzy cognitive maps

This paper proposes a post-hoc explanation method for computing concept attribution in Fuzzy Cognitive Map (FCM) models used for scenario analysis, based on SHapley Additive exPlanations (SHAP) values. The proposal is inspired by the lack of approaches to exploit the often-claimed intrinsic interpretability of FCM models while considering their dynamic properties. Our method uses the initial activation values of concepts as input features, while the outputs are considered as the hidden states produced by the FCM model during the recurrent reasoning process. Hence, the relevance of neural concepts is computed taking into account the model’s dynamic properties and hidden states, which result from the interaction among the initial conditions, the weight matrix, the activation function, and the selected reasoning rule. The proposed post-hoc method can handle situations where the FCM model might not converge or converge to a unique fixed-point attractor where the final activation values of neural concepts are invariant. The effectiveness of the proposed approach is demonstrated through experiments conducted on real-world case studies

Forward Composition Propagation for Explainable Neural Reasoning

This paper proposes an algorithm called Forward Composition Propagation (FCP) to explain the predictions of feed-forward neural networks operating on structured classification problems. In the proposed FCP algorithm, each neuron is described by a composition vector indicating the role of each problem feature in that neuron. Composition vectors are initialized using a given input instance and subsequently propagated through the whole network until reaching the output layer. The sign of each composition value indicates whether the corresponding feature excites or inhibits the neuron, while the absolute value quantifies its impact. The FCP algorithm is executed on a post-hoc basis, i.e., once the learning process is completed. Aiming to illustrate the FCP algorithm, this paper develops a case study concerning bias detection in a fairness problem in which the ground truth is known. The simulation results show that the composition values closely align with the expected behavior of protected features. The source code and supplementary material for this paper are available at https://github.com/igraugar/fcp

Online learning of windmill time series using Long Short-term Cognitive Networks

Forecasting windmill time series is often the basis of other processes such as anomaly detection, health monitoring, or maintenance scheduling. The amount of data generated on windmill farms makes online learning the most viable strategy to follow. Such settings require retraining the model each time a new batch of data is available. However, update the model with the new information is often very expensive to perform using traditional Recurrent Neural Networks (RNNs). In this paper, we use Long Short-term Cognitive Networks (LSTCNs) to forecast windmill time series in online settings. These recently introduced neural systems consist of chained Short-term Cognitive Network blocks, each processing a temporal data chunk. The learning algorithm of these blocks is based on a very fast, deterministic learning rule that makes LSTCNs suitable for online learning tasks. The numerical simulations using a case study with four windmills showed that our approach reported the lowest forecasting errors with respect to a simple RNN, a Long Short-term Memory, a Gated Recurrent Unit, and a Hidden Markov Model. What is perhaps more important is that the LSTCN approach is significantly faster than these state-of-the-art models

Communication improvements for intelligent systems in microgrids - Part I & II

This paper proposes the best architecture for intelligent microgrid applications based on latency, QoS, bandwidth and capital cost, to improve control and operation. In addition, the fundamentals of communications and control strategies for intelligent microgrids and electric vehicles are described. The results show that communication technology affects the performance of control applications and the smartness of the grid, which causes poor quality of service.CONACYT – Consejo Nacional de Ciencia y Tecnologí

Quasi-static Flow Model for Predicting the Extreme Values of Air Pocket Pressure in Draining and Filling Operations in Single Water Installations

[EN] Inertial models have been used by researchers to simulate the draining and filling processes in water pipelines, based on the evolution of the main hydraulic and thermodynamic variables. These models use complex differential equations, which are solved using advanced numerical codes. In this study, a quasi-static flow model is developed to study these operations in hydraulic installations. The quasi-static flow model represents a simplified formulation compared with inertial flow models, in which its numerical resolution is easier because only algebraic equations must be addressed. Experimental measurements of air pocket pressure patterns were conducted in a 4.36 m long single pipeline with an internal diameter of 42 mm. Comparisons between measured and computed air pocket pressure oscillations indicate how the quasi-static flow model can predict extreme values of air pocket pressure for experimental runs, demonstrating the possibility of selecting stiffness and pipe classes in actual pipelines using this model. Two case studies were analysed to determine the behaviour of the quasi-static flow model in large water pipelines.This research and the APC were funded by the Comision Nacional de Investigacion Cientifica y Tecnologica (Conicyt), grant number 1180660.Coronado-Hernández, ÓE.; Fuertes-Miquel, VS.; Mora-Meliá, D.; Salgueiro, Y. (2020). Quasi-static Flow Model for Predicting the Extreme Values of Air Pocket Pressure in Draining and Filling Operations in Single Water Installations. Water. 12(3):1-16. https://doi.org/10.3390/w12030664S116123Abreu, J., Cabrera, E., Izquierdo, J., & García-Serra, J. (1999). Flow Modeling in Pressurized Systems Revisited. Journal of Hydraulic Engineering, 125(11), 1154-1169. doi:10.1061/(asce)0733-9429(1999)125:11(1154)Izquierdo, J., Fuertes, V. S., Cabrera, E., Iglesias, P. L., & Garcia-Serra, J. (1999). Pipeline start-up with entrapped air. Journal of Hydraulic Research, 37(5), 579-590. doi:10.1080/00221689909498518Simpson, A. R., & Wylie, E. B. (1991). Large Water‐Hammer Pressures for Column Separation in Pipelines. Journal of Hydraulic Engineering, 117(10), 1310-1316. doi:10.1061/(asce)0733-9429(1991)117:10(1310)Zhou, L., Liu, D., Karney, B., & Wang, P. (2013). Phenomenon of White Mist in Pipelines Rapidly Filling with Water with Entrapped Air Pockets. Journal of Hydraulic Engineering, 139(10), 1041-1051. doi:10.1061/(asce)hy.1943-7900.0000765Zhou, L., & Liu, D. (2013). Experimental investigation of entrapped air pocket in a partially full water pipe. Journal of Hydraulic Research, 51(4), 469-474. doi:10.1080/00221686.2013.785985Coronado-Hernández, O., Fuertes-Miquel, V., Besharat, M., & Ramos, H. (2017). Experimental and Numerical Analysis of a Water Emptying Pipeline Using Different Air Valves. Water, 9(2), 98. doi:10.3390/w9020098Coronado-Hernández, Ó. E., Besharat, M., Fuertes-Miquel, V. S., & Ramos, H. M. (2019). Effect of a Commercial Air Valve on the Rapid Filling of a Single Pipeline: a Numerical and Experimental Analysis. Water, 11(9), 1814. doi:10.3390/w11091814Vasconcelos, J. G., & Wright, S. J. (2008). Rapid Flow Startup in Filled Horizontal Pipelines. Journal of Hydraulic Engineering, 134(7), 984-992. doi:10.1061/(asce)0733-9429(2008)134:7(984)Fuertes-Miquel, V. S., Coronado-Hernández, O. E., Iglesias-Rey, P. L., & Mora-Meliá, D. (2018). Transient phenomena during the emptying process of a single pipe with water–air interaction. Journal of Hydraulic Research, 57(3), 318-326. doi:10.1080/00221686.2018.1492465Fuertes-Miquel, V. S., Coronado-Hernández, O. E., Mora-Meliá, D., & Iglesias-Rey, P. L. (2019). Hydraulic modeling during filling and emptying processes in pressurized pipelines: a literature review. Urban Water Journal, 16(4), 299-311. doi:10.1080/1573062x.2019.1669188Besharat, M., Coronado-Hernández, O. E., Fuertes-Miquel, V. S., Viseu, M. T., & Ramos, H. M. (2018). Backflow air and pressure analysis in emptying a pipeline containing an entrapped air pocket. Urban Water Journal, 15(8), 769-779. doi:10.1080/1573062x.2018.1540711Besharat, M., Coronado-Hernández, O. E., Fuertes-Miquel, V. S., Viseu, M. T., & Ramos, H. M. (2019). Computational fluid dynamics for sub-atmospheric pressure analysis in pipe drainage. Journal of Hydraulic Research, 58(4), 553-565. doi:10.1080/00221686.2019.1625819Laanearu, J., Annus, I., Koppel, T., Bergant, A., Vučković, S., Hou, Q., … van’t Westende, J. M. C. (2012). Emptying of Large-Scale Pipeline by Pressurized Air. Journal of Hydraulic Engineering, 138(12), 1090-1100. doi:10.1061/(asce)hy.1943-7900.0000631Tijsseling, A. S., Hou, Q., Bozkuş, Z., & Laanearu, J. (2015). Improved One-Dimensional Models for Rapid Emptying and Filling of Pipelines. Journal of Pressure Vessel Technology, 138(3). doi:10.1115/1.4031508Malekpour, A., Karney, B. W., & Nault, J. (2016). Physical Understanding of Sudden Pressurization of Pipe Systems with Entrapped Air: Energy Auditing Approach. Journal of Hydraulic Engineering, 142(2), 04015044. doi:10.1061/(asce)hy.1943-7900.0001067Noto, L., & Tucciarelli, T. (2001). DORA Algorithm for Network Flow Models with Improved Stability and Convergence Properties. Journal of Hydraulic Engineering, 127(5), 380-391. doi:10.1061/(asce)0733-9429(2001)127:5(380)Zhou, L., Liu, D., & Ou, C. (2011). Simulation of Flow Transients in a Water Filling Pipe Containing Entrapped Air Pocket with VOF Model. Engineering Applications of Computational Fluid Mechanics, 5(1), 127-140. doi:10.1080/19942060.2011.11015357SaemI, S., Raisee, M., Cervantes, M. J., & Nourbakhsh, A. (2018). Computation of two- and three-dimensional water hammer flows. Journal of Hydraulic Research, 57(3), 386-404. doi:10.1080/00221686.2018.1459892Apollonio, C., Balacco, G., Fontana, N., Giugni, M., Marini, G., & Piccinni, A. (2016). Hydraulic Transients Caused by Air Expulsion During Rapid Filling of Undulating Pipelines. Water, 8(1), 25. doi:10.3390/w8010025Wang, L., Wang, F., Karney, B., & Malekpour, A. (2017). Numerical investigation of rapid filling in bypass pipelines. Journal of Hydraulic Research, 55(5), 647-656. doi:10.1080/00221686.2017.1300193Coronado-Hernández, O. E., Fuertes-Miquel, V. S., Besharat, M., & Ramos, H. M. (2018). Subatmospheric pressure in a water draining pipeline with an air pocket. Urban Water Journal, 15(4), 346-352. doi:10.1080/1573062x.2018.1475578Ramezani, L., Karney, B., & Malekpour, A. (2016). Encouraging Effective Air Management in Water Pipelines: A Critical Review. Journal of Water Resources Planning and Management, 142(12), 04016055. doi:10.1061/(asce)wr.1943-5452.0000695Martins, S. C., Ramos, H. M., & Almeida, A. B. (2015). Conceptual analogy for modelling entrapped air action in hydraulic systems. Journal of Hydraulic Research, 53(5), 678-686. doi:10.1080/00221686.2015.1077353Zhou, F., Hicks, F. E., & Steffler, P. M. (2002). Transient Flow in a Rapidly Filling Horizontal Pipe Containing Trapped Air. Journal of Hydraulic Engineering, 128(6), 625-634. doi:10.1061/(asce)0733-9429(2002)128:6(625)Cabrera, E., Abreu, J., Pérez, R., & Vela, A. (1992). Influence of Liquid Length Variation in Hydraulic Transients. Journal of Hydraulic Engineering, 118(12), 1639-1650. doi:10.1061/(asce)0733-9429(1992)118:12(1639

Sistema detección de intrusión para microrredes con el protocolo DNP3

88 p.La seguridad en las redes de datos es una de las principales necesidades de la mayoría de las industrias u organizaciones tecnológicas de un país. Los avances científicos dentro de las microrredes eléctricas brindan numerosos beneficios a la industria eléctrica. Sin embargo, la mayor disponibilidad de datos, las nuevas tecnologías de comunicación utilizadas y los altos índices de automatización, permiten que los ciberatacantes puedan realizar diferentes ataques cibernéticos en la industria. Cortes del suministro eléctrico de manera prolongada, ocasionará pérdidas significativas a las instituciones, afectará de manera directa a los usuarios y degradará la confiabilidad de la red eléctrica. De esta manera, las empresas encargadas del despliegue de las microrredes están potenciando alternativas para detectar la presencia de agentes externos al sistema eléctrico y tomar las medidas para minimizar el riesgo. Con el propósito de desarrollar un sistema de comunicación confiable dentro de una microrred, en esta investigación se propone utilizar un sistema de detección de intrusiones (IDS) basado en técnicas de inteligencia computacional. El aporte fundamental de esta investigación radica en la configuración un IDS sobre el protocolo de comunicaciones DNP3 utilizado para el intercambio de mensajes de control y datos, en microrredes eléctricas. Los datos utilizados fueron obtenidos desde una fuente disponible en internet, con datos procesados el año 2016, donde se registraron ataques a través del protocolo DNP3. Estos datos fueron organizados y se procesaron de tal manera que se extrajeron las características del protocolo que interesaban y se utilizaron para poder realizar las pruebas correspondientes. Se utilizaron 70 mil registros y un total de 434.270 tramas, sobre los cuales se aplicó un proceso de preparación y clasificación, separando las tramas de datos normales con las de datos anómalos para la ejecución de las pruebas. El sistema de detección de intrusiones también ayuda a la notificación oportuna de incidentes de seguridad, las cuales son mostradas a través de alertas de diferentes tipos, a las personas responsables. Además se desarrolló una aplicación web y se configuró el servicio SMTP para mostrar y enviar notificaciones respectivamente cuando se detecte una alerta. Se comprobó que el sistema de detección de intrusos Snort, para una red basada en el protocolo de comunicación DNP3, logra índices de detección por encima de un 98%. Esto es particularmente útil en sistemas de control como el caso de las microrredes eléctricas, ya que permite elevar la disponibilidad, al detectar intrusiones en el sistema de una manera efectiva

Pumping Station Design in Water Distribution Networks Considering the Optimal Flow Distribution between Sources and Capital and Operating Costs

[EN] The investment and operating costs of pumping stations in drinking water distribution networks are some of the highest public costs in urban sectors. Generally, these systems are designed based on extreme scenarios. However, in periods of normal operation, extra energy is produced, thereby generating excess costs. To avoid this problem, this work presents a new methodology for the design of pumping stations. The proposed technique is based on the use of a setpoint curve to optimize the operating and investment costs of a station simultaneously. According to this purpose, a novel mathematical optimization model is developed. The solution output by the model includes the selection of the pumps, the dimensions of pipelines, and the optimal flow distribution among all water sources for a given network. To demonstrate the advantages of using this technique, a case study network is presented. A pseudo-genetic algorithm (PGA) is implemented to resolve the optimization model. Finally, the obtained results show that it is possible to determine the full design and operating conditions required to achieve the lowest cost in a multiple pump station network.This work was supported by the Program Fondecyt Regular (Project N. 1210410) of the Agencia Nacional de Investigación y Desarrollo (ANID), Chile. It is also supported by CONICYT PFCHA/DOCTORADO BECAS CHILE/2018-21182013.Gutiérrez-Bahamondes, JH.; Mora-Meliá, D.; Iglesias Rey, PL.; Martínez-Solano, FJ.; Salgueiro, Y. (2021). Pumping Station Design in Water Distribution Networks Considering the Optimal Flow Distribution between Sources and Capital and Operating Costs. Water. 13(21):1-14. https://doi.org/10.3390/w13213098S114132

jHawanet: an open-source project for the implementation and assessment of multi-objective evolutionary algorithms on water distribution networks

[EN] Efficient design and management of water distribution networks is critical for conservation of water resources and minimization of both energy requirements and maintenance costs. Several computational routines have been proposed for the optimization of operational parameters that govern such networks. In particular, multi-objective evolutionary algorithms have proven to be useful both properly describing a network and optimizing its performance. Despite these computational advances, practical implementation of multi-objective optimization algorithms for water networks is an abstruse subject for researchers and engineers, particularly since efficient coupling between multi-objective algorithms and the hydraulic network model is required. Further, even if the coupling is successfully implemented, selecting the proper set of multi-objective algorithms for a given network, and addressing the quality of the obtained results (i.e., the approximate Pareto frontier) introduces additional complexities that further hinder the practical application of these algorithms. Here, we present an open-source project that couples the EPANET hydraulic network model with the jMetal framework for multi-objective optimization, allowing flexible implementation and comparison of different metaheuristic optimization algorithms through statistical quality assessment. Advantages of this project are discussed by comparing the performance of different multi-objective algorithms (i.e., NSGA-II, SPEA2, SMPSO) on case study water pump networks available in the literatureThis research and the APC were funded by the Comision Nacional de Investigacion Cientifica y Tecnologica (Conicyt), grant number 1180660Gutierrez-Bahamondes, JH.; Salgueiro, Y.; Silva-Rubio, SA.; Alsina, MA.; Mora-Melia, D.; Fuertes-Miquel, VS. (2019). jHawanet: an open-source project for the implementation and assessment of multi-objective evolutionary algorithms on water distribution networks. Water. 11(10):1-17. https://doi.org/10.3390/w111020181171110Wang, Y., Hua, Z., & Wang, L. (2018). Parameter Estimation of Water Quality Models Using an Improved Multi-Objective Particle Swarm Optimization. Water, 10(1), 32. doi:10.3390/w10010032Letting, L., Hamam, Y., & Abu-Mahfouz, A. (2017). Estimation of Water Demand in Water Distribution Systems Using Particle Swarm Optimization. Water, 9(8), 593. doi:10.3390/w9080593Ngamalieu-Nengoue, U. A., Martínez-Solano, F. J., Iglesias-Rey, P. L., & Mora-Meliá, D. (2019). Multi-Objective Optimization for Urban Drainage or Sewer Networks Rehabilitation through Pipes Substitution and Storage Tanks Installation. Water, 11(5), 935. doi:10.3390/w11050935Morley, M. ., Atkinson, R. ., Savić, D. ., & Walters, G. . (2001). GAnet: genetic algorithm platform for pipe network optimisation. Advances in Engineering Software, 32(6), 467-475. doi:10.1016/s0965-9978(00)00107-1Van Thienen, P., & Vertommen, I. (2015). Gondwana: A Generic Optimization Tool for Drinking Water Distribution Systems Design and Operation. Procedia Engineering, 119, 1212-1220. doi:10.1016/j.proeng.2015.08.978Mala-Jetmarova, H., Sultanova, N., & Savic, D. (2017). Lost in optimisation of water distribution systems? A literature review of system operation. Environmental Modelling & Software, 93, 209-254. doi:10.1016/j.envsoft.2017.02.009Durillo, J. J., & Nebro, A. J. (2011). jMetal: A Java framework for multi-objective optimization. Advances in Engineering Software, 42(10), 760-771. doi:10.1016/j.advengsoft.2011.05.014Ravber, M., Mernik, M., & Črepinšek, M. (2017). The impact of Quality Indicators on the rating of Multi-objective Evolutionary Algorithms. Applied Soft Computing, 55, 265-275. doi:10.1016/j.asoc.2017.01.03

Explicit methods for attribute weighting in multi-attribute decision-making: a review study

Attribute weighting is a key aspect when modeling multi-attribute decision analysis problems. Despite the large number of proposals reported in the literature, reaching a consensus on the most convenient method for a certain scenario is difficult, if not impossible. As a first contribution of this paper, we propose a categorization of existing methodologies, which goes beyond the current taxonomy (subjective, objective, hybrid). As a second contribution, supported by the new categorization, we survey and critically discuss the explicit weighting methods (which are closely related to the subjective ones). The critical discussion allows evaluating how much a solution can deviate from the expected one if no foresight is taken. As a final contribution, we summarize the main drawbacks from a global perspective and propose some insights to correct them. Such a discussion attempts to improve the reliability of decision support systems involving human experts