This paper develops a mathematically grounded neuro-fuzzy control framework for IoT-enabled irrigation systems in precision agriculture. A discrete-time, physically motivated model of soil moisture is formulated to capture the nonlinear water dynamic...
Several crucial system design and deployment decisions, including workload management, sizing, capacity planning, and dynamic rule generation in dynamic systems such as computers, depend on predictive analysis of resource consumption. An analysis of...
The challenge for our paper consists in controlling the performance of the future state of a microgrid with energy produced from renewable energy sources. The added value of this proposal consists in identifying the most used criteria, related to eac...
Energy policies and economies of scale have promoted the expansion of renewable energy sources, leading to the displacement of conventional generation units and a consequent reduction in system inertia. Low inertia amplifies frequency deviations in r...
Neuro-fuzzy systems (NFS), as part of artificial intelligence (AI) techniques, have become popular in modeling and forecasting applications in many fields in the past few decades. NFS are powerful tools for mapping complex associations between inputs...
In this study, a hybrid method based on the marine predators algorithm (MPA) and adaptive neuro-fuzzy inference system (ANFIS) is presented to identify nonlinear systems exhibiting symmetrical or asymmetrical behavior. In other words, the antecedent...
A modified onboard neuro-fuzzy adaptive (NFA) helicopter turboshaft engine (HTE) automatic control system (ACS) is proposed, which is based on a circuit consisting of a research object, a regulator, an emulator, a compensator, and an observer unit. I...
Gas-insulated switchgear malfunctions during power system operation may occur due to electrical, thermal, or human errors in the manufacturing process. The leading causes of insulation deterioration of gas-insulated switchgear are discharging along t...
In the current smart grid scenario, the evolution of a proficient and robust maximum power point tracking (MPPT) algorithm for a PV subsystem has become imperative due to the fluctuating meteorological conditions. In this paper, an adaptive feedback...
Electricity load forecasting plays a paramount role in capacity planning, scheduling, and the operation of power systems. Reliable and accurate planning and prediction of electricity load are therefore vital. In this study, a novel approach for forec...
The power output forecasting of the photovoltaic (PV) system is essential before deciding to install a photovoltaic system in Nakhon Ratchasima, Thailand, due to the uneven power production and unstable data. This research simulates the power output...
The surface contamination of electrical insulators can increase the electrical conductivity of these components, which may lead to faults in the electrical power system. During inspections, ultrasound equipment is employed to detect defective insulat...
Wind turbines are the most frequently used objects of renewable energy today. However, issues that arise during their operation can greatly affect their effectiveness. Blade erosion, cracks, and other defects can slash turbine performance while also...
This article uses machine learning techniques as fuzzy and neuro-fuzzy ANFISs, to develop and compare prediction models capable of relating pregnant women’s exposure to air pollutants, such as Nitrogen Dioxide and Particulate Matter, the mother...
The myoelectric signal reflects the electrical activity of skeletal muscles and contains information about the structure and function of the muscles which make different parts of the body move. Advances in engineering have extended electromyography b...
This paper investigates the energy management system (EMS) of a conventional autonomous vehicle, with a view to enhance its powertrain efficiency. The designed EMS includes two neuro-fuzzy (NF) systems to produce the optimal torque of the engine. Thi...
In this paper, a method to extract features of the environment based on ultrasonic sensors is presented. A 3D model of a set of sonar systems and a workplace has been developed. The target of this approach is to extract in a short time, while the veh...
In this paper, an adaptive depth and heading control of an autonomous underwater vehicle using the concept of an adaptive neuro-fuzzy inference system (ANFIS) is designed. The autonomous underwater vehicle dynamics have six degrees of freedom, which...
We propose an adaptive neuro-fuzzy inference system (ANFIS) with an incremental tree structure based on a context-based fuzzy C-means (CFCM) clustering process. ANFIS is a combination of a neural network with the ability to learn, adapt and compute,...
Agriculture is essential for food production and raw materials. A key aspect of this sector is harvest, the stage at which the commercial part of the plant is separated. Timely harvesting minimizes post-harvest losses, preserves product quality, and...
Although the deep neural network has a strong fitting ability, it is difficult to be applied to safety-critical fields because of its poor interpretability. Based on the adaptive neuro-fuzzy inference system (ANFIS) and the concept of residual networ...
The fire behavior of materials is usually modeled on the basis of fire physics and material composition. However, significant strides have been made recently in applying soft computing methods such as artificial intelligence in flammability studies....
Estimating groundwater recharge using mathematical models such as water budget or soil water balance method has been proved to be very difficult due to the complex, uncertain multidimensional nature of the process, despite the simplicity of the conce...
Hydropower is among the cleanest sources of energy. However, the rate of hydropower generation is profoundly affected by the inflow to the dam reservoirs. In this study, the Grey wolf optimization (GWO) method coupled with an adaptive neuro-fuzzy inf...
In the recent past, a few fire warning and alarm systems have been presented based on a combination of a smoke sensor and an alarm device to design a life-safety system. However, such fire alarm systems are sometimes error-prone and can react to non-...
This paper presents a method to detect and classify the high impedance fault that occur in the medium voltage (MV) distribution network using discrete wavelet transform (DWT) and adaptive neuro-fuzzy inference system (ANFIS). The network is designed...
Predicting the mechanical properties of Additive Manufacturing (AM) parts is a complex task due to the intricate nature of the manufacturing processes. This study presents a novel application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) to pr...
This study is dedicated to modeling the spatial variation in COVID-19 prevalence using the adaptive neuro-fuzzy inference system (ANFIS) when dealing with nonlinear relationships, especially useful for small areas or small sample size problems. We co...
The application of wireless sensor networks (WSNs) in smart agriculture requires accurate path loss prediction to determine the coverage area and system capacity. However, fast fading from environment changes, such as leaf movement, unsymmetrical tre...
In the realm of urban geotechnical infrastructure development, accurate estimation of the California Bearing Ratio (CBR), a key indicator of the strength of unbound granular material and subgrade soil, is paramount for pavement design. Traditional la...
Precise force tracking and overshoot suppression are critical for manipulator dynamic contact tasks, especially in unstructured environments such as complex surface cleaning that rely on dynamic feedback from force sensors. Traditional impedance cont...
This study describes the performance assessment of the Huangpu Bridge in Guangzhou, China based on long-term monitoring in real-time by the kinematic global positioning system (RTK-GPS) technique. Wavelet transformde-noising is applied to filter the...
Understanding the relationships among CO2 emissions, energy consumption, and economic growth helps nations to develop energy sources and formulate energy policies in order to enhance sustainable development. The present research is aimed at developin...
This article presents an ultramodern modelling algorithm for predicting the remnant cellulose life cycle for oil-submerged power transformers based on the adaptive neuro-fuzzy interference system (ANFIS). The polymer characteristics, degree of polyme...
This study employs an adaptive neuro-fuzzy inference system (ANFIS) to identify critical success factors (CSFs) crucial for the success of pavement construction projects. Challenges such as construction cost delays, budget overruns, disputes, claims,...
Circulating Fluidized Bed gasifiers are widely used in industry to convert solid fuel into liquid fuel. The Artificial Neural Network and neuro-fuzzy algorithm have immense potential to improve the efficiency of the gasifier. The main focus of this a...
The existing literature predominantly concentrates on the utilization of the gradient descent algorithm for control systems’ design in power systems for stability enhancement. In this paper, various flavors of the Conjugate Gradient (CG) algorithm ha...
In order to predict the dilution characteristics of vertical buoyant jets constrained by lateral obstructions, we propose a new method based on a commonly used machine learning algorithm: the adaptive neuro-fuzzy inference system (ANFIS). By using ex...
This study focuses on the important issue of predicting electricity load for efficient energy management. To achieve this goal, different statistical methods were compared, and results over time were analyzed using various ratios and layers for train...
The primary purpose of this study was to apply structural equation modeling (SEM) integrated with an adaptive neuro-fuzzy inference system (ANFIS) approach to model the safety culture of the petrochemical industry of Japan. Workers from five companie...
In the current era of e-mobility and for the planning of sustainable grid infrastructures, developing new efficient tools for real-time grid performance monitoring is essential. Thus, this paper presents the prediction of the voltage stability margin...
The present study elaborates the suitability of the artificial neural network (ANN) and adaptive neuro-fuzzy interface system (ANFIS) to predict the thermal performances of the thermoelectric generator system for waste heat recovery. Six ANN models a...
Typhoon intensity forecast is an important issue. The objective of this study is to construct a 5-day 12-hourly typhoon intensity forecast model based on the adaptive neuro-fuzzy inference systems (ANFIS) to improve the typhoon intensity forecast in...
In this research, an effective application and performance assessment of the Neuro-Fuzzy Controller (NFC) damping controller is designed to replace a single machine infinite bus (SMIB) power system stabilizer (PSS), and coordinated multi PSSs in larg...
The research paper proposes a novel denoising method to improve the outcome of heart-sound (HS)-based heart-condition identification by applying the dual-tree complex wavelet transform (DTCWT) together with the adaptive neuro-fuzzy inference System (...
In this study, the durability of polyvinyl alcohol fiber-reinforced cementitious composite containing nano-SiO2 was evaluated using the adaptive neuro-fuzzy inference system (ANFIS). According to the structural characteristics of the cementitious com...
Tracking the rheological properties of the drilling fluid is a key factor for the success of the drilling operation. The main objective of this paper is to relate the most frequent mud measurements (every 15 to 20 min) as mud weight (MWT) and Marsh f...
The shift from fossil fuel to more renewable electricity generation will require the broader implementation of Demand Side Response (DSR) into the grid. Utility processes in industry are suited for this, having a large thermal time constant or buffer...
Increasing economic and population growth has led to a rise in electricity consumption. Consequently, electrical utility firms must have a proper energy management strategy in place to improve citizens’ quality of life and ensure an organizatio...
Intelligent voltage stability monitoring remains an essential feature of modern research into secure operations of power system networks. This research developed an adaptive neuro-fuzzy expert system (ANFIS)-based predictive model to validate the via...
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