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A Layered Spiking Neural System for Classification Problems (2022)
Journal Article
Zhang, G., Zhang, X., Rong, H., Paul, P., Zhu, M., Neri, F., & Ong, Y. (2022). A Layered Spiking Neural System for Classification Problems. International Journal of Neural Systems, 32(8), Article 2250023. https://doi.org/10.1142/S012906572250023X

Biological brains have a natural capacity for resolving certain classification tasks. Studies on biologically plausible spiking neurons, architectures and mechanisms of artificial neural systems that closely match biological observations while giving... Read More about A Layered Spiking Neural System for Classification Problems.

A self-adaptive multi-objective feature selection approach for classification problems (2021)
Journal Article
Xue, Y., Zhu, H., & Neri, F. (2022). A self-adaptive multi-objective feature selection approach for classification problems. Integrated Computer-Aided Engineering, 29(1), 3-21. https://doi.org/10.3233/ICA-210664

In classification tasks, feature selection (FS) can reduce the data dimensionality and may also improve classification accuracy, both of which are commonly treated as the two objectives in FS problems. Many meta-heuristic algorithms have been applied... Read More about A self-adaptive multi-objective feature selection approach for classification problems.

Generalised Pattern Search with Restarting Fitness Landscape Analysis (2021)
Journal Article
Neri, F. (2022). Generalised Pattern Search with Restarting Fitness Landscape Analysis. SN Computer Science, 3(2), Article 110. https://doi.org/10.1007/s42979-021-00989-8

Fitness landscape analysis for optimisation is a technique that involves analysing black-box optimisation problems to extract pieces of information about the problem, which can beneficially inform the design of the optimiser. Thus, the design of the... Read More about Generalised Pattern Search with Restarting Fitness Landscape Analysis.

Self-Adaptive Particle Swarm Optimization-Based Echo State Network for Time Series Prediction (2021)
Journal Article
Xue, Y., Zhang, Q., & Neri, F. (2021). Self-Adaptive Particle Swarm Optimization-Based Echo State Network for Time Series Prediction. International Journal of Neural Systems, 31(12), Article 2150057. https://doi.org/10.1142/s012906572150057x

Echo state networks (ESNs), belonging to the family of recurrent neural networks (RNNs), are suitable for addressing complex nonlinear tasks due to their rich dynamic characteristics and easy implementation. The reservoir of the ESN is composed of a... Read More about Self-Adaptive Particle Swarm Optimization-Based Echo State Network for Time Series Prediction.

Global Rate-distortion Optimization of Video-based Point Cloud Compression with Differential Evolution (2021)
Conference Proceeding
Yuan, H., Hamzaoui, R., Neri, F., Yang, S., & Wang, T. (2022). Global Rate-distortion Optimization of Video-based Point Cloud Compression with Differential Evolution. In 2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP). https://doi.org/10.1109/MMSP53017.2021.9733714

In video-based point cloud compression (V-PCC), one geometry video and one color video are generated from a dynamic point cloud. Then, the two videos are compressed independently using a state-of-the-art video coder. In the Moving Picture Experts Gro... Read More about Global Rate-distortion Optimization of Video-based Point Cloud Compression with Differential Evolution.

SPMS-ALS: A Single-Point Memetic structure with accelerated local search for instance reduction (2021)
Journal Article
Le, H. L., Neri, F., & Triguero, I. (2022). SPMS-ALS: A Single-Point Memetic structure with accelerated local search for instance reduction. Swarm and Evolutionary Computation, 69, Article 100991. https://doi.org/10.1016/j.swevo.2021.100991

Real-world optimisation problems pose domain specific challenges that often require an ad-hoc algorithmic design to be efficiently addressed. The present paper investigates the optimisation of a key stage in data mining, known as instance reduction,... Read More about SPMS-ALS: A Single-Point Memetic structure with accelerated local search for instance reduction.

Model-Based Rate-Distortion Optimized Video-Based Point Cloud Compression with Differential Evolution (2021)
Conference Proceeding
Yuan, H., Hamzamoui, R., Neri, F., & Yang, S. (2021). Model-Based Rate-Distortion Optimized Video-Based Point Cloud Compression with Differential Evolution. In Image and Graphics (735-747). https://doi.org/10.1007/978-3-030-87355-4_61

The Moving Picture Experts Group (MPEG) video-based point cloud compression (V-PCC) standard encodes a dynamic point cloud by first converting it into one geometry video and one color video and then using a video coder to compress the two video seque... Read More about Model-Based Rate-Distortion Optimized Video-Based Point Cloud Compression with Differential Evolution.

Covariance Pattern Search with Eigenvalue-determined Radii (2021)
Conference Proceeding
Neri, F., & Zhou, Y. (2021). Covariance Pattern Search with Eigenvalue-determined Radii. In Proceedings of the IEEE Congress on Evolutionary Computation 2021 (335-342). https://doi.org/10.1109/CEC45853.2021.9505002

Effective implementations of Memetic Algorithms often integrate, within their design, problem-based pieces of information. When no information is known, an efficient MA can still be designed after a preliminary analysis of the problem. This approach... Read More about Covariance Pattern Search with Eigenvalue-determined Radii.

A Multi-Objective Evolutionary Approach Based on Graph-in-Graph for Neural Architecture Search of Convolutional Neural Networks (2021)
Journal Article
Xue, Y., Jiang, P., Neri, F., & Liang, J. (2021). A Multi-Objective Evolutionary Approach Based on Graph-in-Graph for Neural Architecture Search of Convolutional Neural Networks. International Journal of Neural Systems, 31(09), Article 2150035. https://doi.org/10.1142/S0129065721500350

With the development of deep learning, the design of an appropriate network structure becomes fundamental. In recent years, the successful practice of Neural Architecture Search (NAS) has indicated that an automated design of the network structure ca... Read More about A Multi-Objective Evolutionary Approach Based on Graph-in-Graph for Neural Architecture Search of Convolutional Neural Networks.

Intrusion Detection System Based on an Updated ANN Model (2021)
Conference Proceeding
Xue, Y., Onzo, B., & Neri, F. (2021). Intrusion Detection System Based on an Updated ANN Model. In Y. Tan, & Y. Shi (Eds.), Advances in Swarm Intelligence : 12th International Conference, ICSI 2021, Qingdao, China, July 17–21, 2021, Proceedings, Part II (472-479). https://doi.org/10.1007/978-3-030-78811-7_44

An intrusion detection system (IDS) is a software application or hardware appliance that monitors traffic on networks and systems to search for suspicious activity and known threats, sending up alerts when it finds such items. In these recent years,... Read More about Intrusion Detection System Based on an Updated ANN Model.

Multi-Objective Feature Selection With Missing Data in Classification (2021)
Journal Article
Xue, Y., Tang, Y., Xu, X., Liang, J., & Neri, F. (2022). Multi-Objective Feature Selection With Missing Data in Classification. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(2), 355-364. https://doi.org/10.1109/TETCI.2021.3074147

Feature selection (FS) is an important research topic in machine learning. Usually, FS is modelled as a bi-objective optimization problem whose objectives are: 1) classification accuracy; 2) number of features. One of the main issues in real-world ap... Read More about Multi-Objective Feature Selection With Missing Data in Classification.

Adaptive Covariance Pattern Search (2021)
Book Chapter
Neri, F. (2021). Adaptive Covariance Pattern Search. In P. A. Castillo, & J. L. Jiménez Laredo (Eds.), Applications of Evolutionary Computation – 24th International Conference, EvoApplications 2021 (178-193). Springer. https://doi.org/10.1007/978-3-030-72699-7_12

Pattern search is a family of single solution deterministic optimisation algorithms for numerical optimisation. Pattern search algorithms generate a new candidate solution by means of an archive of potential moves, named pattern. This pattern is gen... Read More about Adaptive Covariance Pattern Search.

Generalised Pattern Search Based on Covariance Matrix Diagonalisation (2021)
Journal Article
Neri, F., & Rostami, S. (2021). Generalised Pattern Search Based on Covariance Matrix Diagonalisation. SN Computer Science, 2, Article 171. https://doi.org/10.1007/s42979-021-00513-y

Pattern Search is a family of gradient-free direct search methods for numerical optimisation problems. The characterising feature of pattern search methods is the use of multiple directions spanning the problem domain to sample new candidate solution... Read More about Generalised Pattern Search Based on Covariance Matrix Diagonalisation.

Teaching Mathematics to Computer Scientists: Reflections and a Case Study (2021)
Journal Article
Neri, F. (2021). Teaching Mathematics to Computer Scientists: Reflections and a Case Study. SN Computer Science, 2(2), Article 75. https://doi.org/10.1007/s42979-021-00461-7

Mathematics, despite being the foundation of computer science, is nowadays often considered a totally separate subject. The fact that many jobs in computer science do not explicitly require any specific mathematical knowledge posed questions about th... Read More about Teaching Mathematics to Computer Scientists: Reflections and a Case Study.

A Complete Arithmetic Calculator Constructed from Spiking Neural P Systems and its Application to Information Fusion (2020)
Journal Article
Zhang, G., Rong, H., Paul, P., He, Y., Neri, F., & Pérez-Jiménez, M. J. (2021). A Complete Arithmetic Calculator Constructed from Spiking Neural P Systems and its Application to Information Fusion. International Journal of Neural Systems, 31(1), Article 2050055. https://doi.org/10.1142/S0129065720500550

© World Scientific Publishing Company Several variants of spiking neural P systems (SNPS) have been presented in the literature to perform arithmetic operations. However, each of these variants was designed only for one specific arithmetic operation.... Read More about A Complete Arithmetic Calculator Constructed from Spiking Neural P Systems and its Application to Information Fusion.

An Adaptive Optimization Spiking Neural P System for Binary Problems (2020)
Journal Article
Zhu, M., Yang, Q., Dong, J., Zhang, G., Gou, X., Rong, H., …Neri, F. (2021). An Adaptive Optimization Spiking Neural P System for Binary Problems. International Journal of Neural Systems, 31(1), Article 2050054. https://doi.org/10.1142/S0129065720500549

© 2020 World Scientific Publishing Company. Optimization Spiking Neural P System (OSNPS) is the first membrane computing model to directly derive an approximate solution of combinatorial problems with a specific reference to the 0/1 knapsack problem.... Read More about An Adaptive Optimization Spiking Neural P System for Binary Problems.

On Algorithmic Descriptions and Software Implementations for Multi-objective Optimisation: A Comparative Study (2020)
Journal Article
Rostami, S., Neri, F., & Kiril, G. (2020). On Algorithmic Descriptions and Software Implementations for Multi-objective Optimisation: A Comparative Study. SN Computer Science, 1, https://doi.org/10.1007/s42979-020-00265-1

Multi-objective optimisation is a prominent subfield of optimisa-tion with high relevance in real-world problems, such as engineering design. Over the past two decades a multitude of heuristic algorithms for multi-objective optimisation have been int... Read More about On Algorithmic Descriptions and Software Implementations for Multi-objective Optimisation: A Comparative Study.

Covariance Local Search for Memetic Frameworks: A Fitness Landscape Analysis Approach (2020)
Conference Proceeding
Neri, F., & Zhou, Y. (2020). Covariance Local Search for Memetic Frameworks: A Fitness Landscape Analysis Approach. In 2020 IEEE Congress on Evolutionary Computation (CEC) (1-8). https://doi.org/10.1109/CEC48606.2020.9185548

© 2020 IEEE. The design of each agent composing a Memetic Algorithm (MA) is a delicate task which often requires prior knowledge of the problem to be effective. This paper proposes a method to analyse one feature of the fitness landscape, that is the... Read More about Covariance Local Search for Memetic Frameworks: A Fitness Landscape Analysis Approach.

An Adaptive Memetic P System to Solve the 0/1 Knapsack Problem (2020)
Conference Proceeding
Dong, J., Rong, H., Neri, F., Yang, Q., Zhu, M., & Zhang, G. (2020). An Adaptive Memetic P System to Solve the 0/1 Knapsack Problem. In Proceedings of the 2020 IEEE Congress on Evolutionary Computation (1-8). https://doi.org/10.1109/CEC48606.2020.9185841

© 2020 IEEE. Memetic Algorithms are traditionally composed of an evolutionary framework and one or more local search elements. However, modern generation Memetic Algorithms do not necessarily follow a pre-established scheme and are hybrid structures... Read More about An Adaptive Memetic P System to Solve the 0/1 Knapsack Problem.

Multi-behaviors coordination controller design with enzymatic numerical P systems for robots (2020)
Journal Article
Wang, X., Zhang, G., Gou, X., Paul, P., Neri, F., Rong, H., …Zhang, H. (2021). Multi-behaviors coordination controller design with enzymatic numerical P systems for robots. Integrated Computer-Aided Engineering, 28(2), 119-140. https://doi.org/10.3233/ica-200627

Membrane computing models are parallel and distributed natural computing models. These models are often referred to as P systems. This paper proposes a novel multi-behaviors coordination controller model using enzymatic numerical P systems for autono... Read More about Multi-behaviors coordination controller design with enzymatic numerical P systems for robots.