Results 21 to 30 of about 3,578 (185)

Assessment of the efficiency of educational project management using neuro-fuzzy system [PDF]

E3S Web of Conferences, 2019
The project represents the introduction of elements and methods of artificial intelligence in the work programs of disciplines in the direction of “Management”.
Krichevsky Mikhail, Bydagov Artyr, Martynova Julia   +2 more
doaj   +1 more source

Trajectory Tracking Control of a Manipulator Based on an Adaptive Neuro-Fuzzy Inference System

Applied Sciences, 2023
Taking an intelligent trimming device hydraulic manipulator as the research object, aiming at the uncertainty, nonlinearity and complexity of its system, a trajectory tracking control scheme is studied in this paper.
Jiangyi Han, Fan Wang, Chenxi Sun
doaj   +1 more source

Application of adaptive neuro-fuzzy inference system (ANFIS) to estimate the biochemical oxygen demand (BOD) of Surma River

Journal of King Saud University: Engineering Sciences, 2017
This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) to estimate the biochemical oxygen demand (BOD) of Surma River of Bangladesh. The data sets consist of 10 water quality parameters which include pH, alkalinity (mg/L as
A.A. Masrur Ahmed, Syed Mustakim Ali Shah   +1 more
doaj   +1 more source

Machine learning models for prediction of rainfall over Nigeria

Scientific African, 2022
Investigating climatology and predicting rainfall amounts are crucial for planning and mitigating the risks caused by variable rainfall. This study utilized two multivariate polynomial regressions (MPR) and twelve machine learning algorithms, namely ...
Olusola Samuel Ojo, Samuel Toluwalope Ogunjo   +1 more
doaj   +1 more source

Novel Intelligence ANFIS Technique for Two-Area Hybrid Power System’s Load Frequency Regulation [PDF]

E3S Web of Conferences
The main objective of Load Frequency Control (LFC) is to effectively manage the power output of an electric generator at a designated site, in order to maintain system frequency and tie-line loading within desired limits, in reaction to fluctuations. The
Nireekshana Namburi, Ramachandran R., Narayana G.V.   +2 more
doaj   +1 more source

Comparison of artificial intelligence methods for predicting compressive strength of concrete

Građevinar, 2021
Compressive strength of concrete is an important parameter in concrete design. Accurate prediction of compressive strength of concrete can lower costs and save time.
Mehmet Timur Cihan
doaj   +1 more source

Estimating maximum shear modulus (G) using adaptive neuro-fuzzy inference system (ANFIS)

Soil Dynamics and Earthquake Engineering, 2022
Realistic estimation of soil behavior is dependent on considering very small and small strain domains. Lengthy formulas proposed in the literature have limited predictive power for estimation of maximum shear modulus, G0. The aim of this study is to overcome this drawback.
Ali Vatanshenas, Tim Tapani Länsivaara
openaire   +4 more sources

Sign Language Detection System Using Adaptive Neuro Fuzzy Inference System (ANFIS) Method

Journal of Applied Engineering and Technological Science (JAETS), 2022
Sign language is a language that prioritizes communication with hands, body language, and lip movements to communicate. The deaf are the main group who use this language, often combining hand shape, hand, arm and body orientation and movement, and facial expressions to express their thoughts.
Dadang Mulyana Iskandar, Mesra Betty Yel, Eka Maheswara   +2 more
openaire   +2 more sources

Prediksi Penjualan Barang Menggunakan Metode Adaptive Neuro-Fuzzy Inference System (ANFIS)

Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika, 2016
Prediksi penjualan barang merupakan salah satu cara untuk menjaga stabilitas penjualan barang. Hasil prediksi yang diperoleh dapat dijadikan sebagai pertimbangan untuk mengambil keputusan dalam perencanaan manajemen bisnis. Salah satu metode yang dapat digunakan untuk prediksi adalah Adaptive Neuro-Fuzzy Inference System (ANFIS).
Allyna Virrayyani, Sutikno Sutikno
openaire   +3 more sources

Tractor-Implement Tillage Depth Control Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Proceedings of Engineering and Technology Innovation, 2021
This study presents a design of an adaptive neuro-fuzzy controller for tractors’ tillage operations. Since the classical controllers allows plowing depth errors due to the variations of lands structure, the use of the combined neural networks and fuzzy logic methods decreases these errors.
Aristide Timene, Ndjiya Ngasop, Haman Djalo   +2 more
openaire   +2 more sources