Non-Singleton Type-3 Fuzzy Approach for Flowmeter Fault Detection: Experimental Study in a Gas Industry

Type-3 fuzzy logic and Lyapunov approach for dynamic modeling and analysis of financial markets

Chaos theory offers a new way to investigate variations in financial markets data that cannot be obtained with traditional methods. The primary approach for diagnosing chaos is the existence of positive small Lyapunov views. The positive Lyapunov index indicates the average instability and the system's chaotic nature. The negativity indicates the average rate of non-chaoticness. In this paper, a new approach on basis of type-3 fuzzy logic systems is introduced for modeling the chaotic dynamics of financial data. Also, the attracting dimension tests and the Lyapunov views in the reconstructed dynamics are used for examinations. The simulations on case-study currency market show the applicability and good accuracy of the suggested approach.

Interval Type-3 Fuzzy Adaptation of the Bee Colony Optimization Algorithm for Optimal Fuzzy Control of an Autonomous Mobile Robot

In this study, the first goal is achieving a hybrid approach composed by an Interval Type-3 Fuzzy Logic System (IT3FLS) for the dynamic adaptation of α and β parameters of Bee Colony Optimization (BCO) algorithm. The second goal is, based on BCO, to find the best partition of the membership functions (MFs) of a Fuzzy Controller (FC) for trajectory tracking in an Autonomous Mobile Robot (AMR). A comparative with different types of Fuzzy Systems, such as Fuzzy BCO with Type-1 Fuzzy Logic System (FBCO-T1FLS), Fuzzy BCO with Interval Type-2 Fuzzy Logic System (FBCO-IT2FLS) and Fuzzy BCO with Generalized Type-2 Fuzzy Logic System (FBCO-GT2FLS) is analyzed. A disturbance is added to verify if the FBCO-IT3FLS performance is better when the uncertainty is present. Several performance indices are used; RMSE, MSE and some metrics of control such as, ITAE, IAE, ISE and ITSE to measure the controller’s performance. The experiments show excellent results using FBCO-IT3FLS and are better than FBCO-GT2FLS, FBCO-IT2FLS and FBCO-T1FLS in the adaptation of α and β parameters.

Interval Type-3 Fuzzy Control for Automated Tuning of Image Quality in Televisions

In this article, an intelligent system utilizing type-3 fuzzy logic for automated image quality tuning in televisions is presented. The tuning problem can be formulated as controlling the television imaging system to achieve the requirements of production quality. Previously, the tuning process has been carried out by experts, by manually adjusting the television imaging system on production lines to meet the quality control standards. In this approach, interval type-3 fuzzy logic is utilized with the goal of automating the tuning of televisions manufactured on production lines. An interval type-3 fuzzy approach for image tuning is proposed, so that the best image quality is obtained and, in this way, meet quality requirements. A system based on type-3 fuzzy control is implemented with good simulation results. The validation of the type-3 fuzzy approach is made by comparing the results with human experts on the process of electrical tuning of televisions. The key contribution is the utilization of type-3 fuzzy in the image tuning application, which has not been reported previously in the literature.

A Taxonomy for Threat Actors’ Delivery Techniques

The main contribution of this paper is to provide an accurate taxonomy for delivery techniques, which allows the detection of novel techniques and the identification of appropriate countermeasures. Delivery is a key stage for offensive cyber operations. During delivery, a threat actor tries to gain an initial foothold into the targeted infrastructure. It is the first step of an offensive cyber operation, where the threat actor interacts with its victim in a hostile way; thus, its success is mandatory for the global achievement of the operation. However, delivery techniques are not well structured among the literature, being in many cases a simple list of techniques with which, if one of them is slightly modified by the threat actor, its detection becomes very difficult. This situation hinders the modeling of hostile actors, a fact that makes it difficult to identify countermeasures to detect and neutralize their malicious activities. In this work, we analyze the current delivery techniques’ classification approaches and the problems linked to them. From this analysis, we propose a novel taxonomy that allows the accurate classification of techniques, overcoming the identified problems and allowing both the discovery of new techniques and the detection of gaps in deployed countermeasures. Our proposal significantly reduces the amount of effort needed to identify, analyze, and neutralize hostile activities from advanced threat actors, in particular their initial access stage. It follows a logical structure that can be easy to expand and adapt, and it can be directly used in the industry’s commonly accepted standards, such as MITRE ATT&CK.

A Type-2 Fuzzy Controller for Floating Tension-Leg Platforms in Wind Turbines

This paper proposes a type-2 fuzzy controller for floating tension-leg platforms in wind turbines. Its main objective is to stabilize and control offshore floating wind turbines exposed to oscillating motions. The proposed approach assumes that the dynamics of all units are completely unknown. The latter are approximated using the proposed Sugeno-based type-2 fuzzy approach. A nonlinear Kalman-based algorithm is developed for parameter optimization, and linear matrix inequalities are derived to analyze the system’s stability. For the fuzzy system, both rules and membership functions are optimized. Additionally, in the designed approach, the estimation error of the type-2 fuzzy approach is also considered in the stability analysis. The effectiveness and performance of the proposed approach is assessed using a simulation study of a tension leg platform subject to various disturbance modes.