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Hierarchical Self-Organizing Map as Nonlinear Classificator
Paulo Salgado;Teresa Perdicoullis;P. Lopes dos Santos;Paulo A.F.N. A. Afonso
2024 IEEE 24th International Symposium on Computational Intelligence and Informatics (CINTI)
Year: 2024 | Conference Paper |
Knowledge models often use hierarchical structures, which help break down complex data into manageable components. This enables better understanding and aids in reasoning and decision-making. Hierarchical structures are effective in organizing, managing, and processing complex information. Traditional Self-Organizing Maps are typically flat, two-dimensional grids for visualizing and grouping data....Show More
Autonomous Underwater Vehicles Identification through a Kernel Regressor
Paulo Lopes dos Santos;T-P Azevedo Perdicoúlis;Paulo A. Salgado;Bruno Miguel Ferreira;Nuno A. Cruz
OCEANS 2023 - Limerick
Year: 2023 | Conference Paper |
A kernel regressor to estimate a six-degree-of-fredoom non linear model of an autonomous underwater vehicle is proposed. Although this estimator assumes that the model coefficients are linear combinations of basis functions, it circumvents the problem of specifying the basis functions by using the kernel trick. The Gaussian radial basis function is the chosen kernel, with the Kernel matrix being r...Show More
Modeling and Identification of Li-ion Cells
P. Lopes dos Santos;T.-P. Azevedo Perdicoúlis;Paulo A. Salgado
To develop a full battery model in view to accurate battery management, Li-ion cell dynamics is modelled by a capacitor in series with a simplified Randles circuit. The open circuit voltage is the voltage at the capacitor terminals, allowing, in this way, for the dependence of the open circuit voltage on the state-of-charge to be embedded in its capacitance. The Randles circuit is recognised as a ...Show More
Energy loss optimisation of a robotic arm
Paulo A. Salgado;T-P Azevedo Perdicoúlis;P. Lopes Dos Santos
The use of robots is widely spread across the industry. It is paramount that the robot end-effector tracks a pre-defined trajectory with the lowest energy loss. To contribute to the solution of this problem, the robot trajectory is defined using a tracking parameter which is optimised using the Matlab® fntinunc function and the Particle Swam optimisation algorithm. This approach was tested for a c...Show More
A note on the assessment of a fuzzy derivatives’ time-series predictor
2022 IEEE 10th Jubilee International Conference on Computational Cybernetics and Cyber-Medical Systems (ICCC)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
This note presents the validation of a new methodology for the prediction of complex discrete-time systems or time-series based on a disturbed fuzzy system. This is a generalisation of the traditional fuzzy system that can incorporate in their linguistic fuzzy relationships of the series and is combined with the ODE Taylor method. Disturbed fuzzy systems are capable of approximating regular functi...Show More
Evolutionary Based on Selfish and Altruism Strategies - An Approach to Path Planning Problems
2018 International Conference on Intelligent Systems (IS)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
This paper presents a novel hybrid optimization approach based on a genetic algorithm that combines selfish gene and altruism view of evolution. The purpose of the present research is to develop a new optimization approach to solve path-planning problems, particularly to be used in robot trajectories planning. A brief discussion about selfish versus altruism is made in the perspective of genes, it...Show More
Long-term Memory Structure by Hierarchized SOM
2018 International Conference on Intelligent Systems (IS)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
The most evolved living organisms are characterized by having a sophisticated central nervous system with memorizing capabilities. In its structure are the neuronal cells. Cognitive memory allows the recording, storage, renewal and reading of information. In this work, memory is characterized by its functional and structural aspects and the main mechanisms for the learning and storage processes ar...Show More
Multi-Kalman Filter to Wind Power Forecasting
2018 13th APCA International Conference on Automatic Control and Soft Computing (CONTROLO)
Year: 2018 | Conference Paper |
Cited by: Papers (4)
Wind power forecasting methods are important for the safety of wind renewable energy utilization. However, because wind power is weather dependent and, thus, can be variable and intermittent over different time-scales, it's difficult to build accurate and robust predictive models. In this context, an accurate model is a relevant contribution for a reliable large-scale wind power integration. This ...Show More
Hybrid PSO-cubic spline for autonomous robots optimal trajectory planning
2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)
Year: 2017 | Conference Paper |
Cited by: Papers (2)
This paper presents a new version of the Particle Swarm Optimization algorithm where the particles are replaced by spline functions. The developed algorithm generates smooth motion trajectories with two times continuously differentiable curvature avoiding obstacles placed in the workspace. It can be used for autonomous robot path planning or transport problems. The spline based trajectory generati...Show More
Fall body detection algorithm based on tri-accelerometer sensors
2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)
Year: 2013 | Conference Paper |
Cited by: Papers (4)
In this paper a fall body detection system for a smartphone device is proposed. Its embedded tri-accelerometer sensor was utilized to collect the information about the body motion used by a real-time Pose Body Model (PBM) identified by an Extended Kalman filter algorithm. The PBM supply an estimate about the vertical pose angle value and a neural network is used to detect body fall incidents. More...Show More
Hybrid fuzzy clustering neural networks to wind power generation forecasting
2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)
Year: 2013 | Conference Paper |
Cited by: Papers (3)
Wind power forecasting methods can be used to plan unit commitment, scheduling and dispatch by system operators and electricity traders. Because wind power is weather dependent, and therefore, is variable and intermittent over various time-scales, an accurate forecasting of wind power is recognized as a major contribution for a reliable large-scale wind power integration taking profit of economics...Show More
Image description by Hierarchical Prioritised Fuzzy Systems
2009 IEEE International Conference on Computational Cybernetics (ICCC)
Year: 2009 | Conference Paper |
Cited by: Papers (1)
The inherently hierarchical problem of evaluating the complexity of an image interpretation is of relevance in both computer science and cognitive psychology. In this paper a new method of rule generation for the hierarchical prioritized fuzzy system, HPFS, is proposed, which overcomes the problem of lack of interpretability of most of the traditional fuzzy systems in modelling image. A hierarchic...Show More
Learning Strategy for Optimal Fuzzy Control
2007 IEEE International Symposium on Industrial Electronics
Year: 2007 | Conference Paper |
In this paper, a new scheme of fuzzy optimal control for discrete-time nonlinear systems based on the Pontryagin's Minimum Principle is proposed. Using back propagation from the final co-state error and gradient descent, a method which allows training an adaptive fuzzy inference system to estimate values for the co-state variables converging to the optimal ones is devised. The approach allows find...Show More
Decomposition of a Greenhouse Fuzzy Model
2006 IEEE Conference on Emerging Technologies and Factory Automation
Year: 2006 | Conference Paper |
Cited by: Papers (2)
This paper describes the identification of greenhouse climate processes with multiple fuzzy models by resulting of decomposition of one global (flat) fuzzy model. This process is called separation of linguistic information methodology - SLIM. In this paper, the SLIM methodology is based on fuzzy clustering of fuzzy rules algorithm (FCFRA), which is a generalization of the well-known fuzzy c-means....Show More
Approximation of Derivatives by Fuzzy Systems
2006 3rd International IEEE Conference Intelligent Systems
Year: 2006 | Conference Paper |
Universal approximation is the basis for theoretical research and practical application of fuzzy systems. However, their ability to model static information has been successfully proven and tested, while on the other hand their limitations. In simultaneously modeling dynamical information are well known. So, if a fuzzy model is a correct representation of a process or a function, the derivative of...Show More
This paper presents a fuzzy system-based approach for the approximation of functions with several variables. The improved results on the approximation of regular functions show that fuzzy systems (FS) may keep their semantic structure while approximating, to any degree of accuracy, not only sufficiently regular functions, but also their derivatives. The result is an FS structure containing linguis...Show More
Fuzzy clustering of fuzzy systems
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)
Year: 2004 | Conference Paper |
Cited by: Papers (2)
A fuzzy system entirely characterizes one region of the input-output product space S = U /spl times/ V through a relation expressed by a set of fuzzy rules. Effectively, the fuzzy system establishes a fuzzy map, which assigns for each input fuzzy set in U an output fuzzy set in V. The partition of this product space may be made through the decomposition of the relation. The fuzzy clustering of fuz...Show More
Fuzzy rule clustering
2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236)
Year: 2001 | Conference Paper |
Cited by: Papers (2)
The concept of relevance has been proposed as a measure of the relative importance of sets of rules, allowing the development of a new methodology for organising the linguistic information: SLIM (Separation of Linguistic Information Methodology). Based on this concept and on this methodology, a new fuzzy clustering of fuzzy rules algorithm (FCFRA) is proposed and applied to organise fuzzy IF ... T...Show More
Separation of linguistic information methodology in a fuzzy model
2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236)
Year: 2001 | Conference Paper |
Cited by: Papers (1)
A new methodology for organising the information in different structures was developed: the Separation of Linguistic Information Methodology (SLIM). The concept of relevance, which is in its genesis, was recently proposed, enabling the measurement of the relative importance of rule sets. Based on this methodology, a new algorithm was proposed for the Parallel Collaborative Structure (PCS). As demo...Show More
Process modelling is an important discipline both in science and engineering. The complexity of many real world systems has lead to sophisticated modelling approaches, where both the accuracy and readability of the models are of great importance. Fuzzy modelling is such an approach, which uses well-established machine learning techniques, producing models with the capacity of integrating expert kn...Show More
A new paradigm for the description of image patterns-from pixels to fuzzy sets of rules
Proceedings. Vol.1. Sixth Brazilian Symposium on Neural Networks
Year: 2000 | Conference Paper |
A paradigm for the description of image patterns is presented: it is proposed that images are described by fuzzy IF...THEN rules instead of pixel values. This approach may benefit from recognised fuzzy systems' superior incorporation of measurement uncertainties, greater resources for managing complexity and better ability to deal with natural language. The concept of relevance has been proposed a...Show More
MNet-DACS: multi-level network data acquisition and control system
C. Serodio;J.B. Cunha;M. Cordeiro;A. Valente;R. Morais;P. Salgado;C. Couto
ISIE '97 Proceeding of the IEEE International Symposium on Industrial Electronics
Year: 1997 | Conference Paper |
This paper describes the implementation of a distributed data acquisition network based on the 80C592 microcontroller from Intel. Each station is connected in an hierarchical way to form a tree topology. The lower level network stations, designated by slaves, are dedicate to the data acquisition and the generation of control signals. The upper level, masters, are responsible for the communications...Show More
A computer-based fuzzy temperature controller for environmental chambers
ISIE '97 Proceeding of the IEEE International Symposium on Industrial Electronics
Year: 1997 | Conference Paper |
Cited by: Papers (4)
This paper describes a computer-based temperature control system for an environmental chamber. The identification of the thermal process was made from the analysis of the collected output data in response to random generated input signals. Using this model the optimal linear and nonlinear control strategies were established in order to achieve the desired set-point and to minimize the number of ac...Show More
Solar data acquisition wireless network for agricultural applications
R. Morais;J. Boaventura Cunha;M. Cordeiro;C. Serodio;P. Salgado;C. Couto
Proceedings of 19th Convention of Electrical and Electronics Engineers in Israel
Year: 1996 | Conference Paper |
Cited by: Papers (11)
This paper describes the implementation of a wireless data acquisition network for agricultural applications based on the Microchip PIC16C71, and the Intel 87C592 microcontrollers. The system uses a set of solar powered wireless data-acquisition stations (SPWAS) linked by radio frequency to a base station (BS). The base station has as main functions the control of the data-acquisition stations and...Show More
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