نتایج جستجو برای: neuro fuzzy

تعداد نتایج: 104179  

2013
Ebrahim Mattar

Relating an arm Cartesian space to joint space and arm dynamics, is an essential issue in arm control that has been given a substantial attention by number of researches. Arm inverse kinematic, is a nonlinear relation, and a closed form solution is not a straight forward, or does not even always exist. This research is presenting a practical use of Neuro-Fuzzy system to solve inverse kinematics...

2014
D. G. Harkut

In a real time system contained various type of scheduling algorithms. They are used for determine which processes should be executed by the CPU when there are different processes to be executed. Neuro fuzzy logic approaches are very effective for scheduling real time task. This paper presents a review on scheduling algorithm of real time task. Then, discuss the limitations of EDF algorithm and...

2013
Y. Nahraoui

An Adaptative Neuro-Fuzzy Inference System (ANFIS) is developed to predict the acoustic form function (FF) for an infinite length cylindrical shell excited perpendicularly to its axis. The Wigner-Ville distribution (WVD) is used like a comparison tool between the calculated FF by the analytical method and that predicted by the neuro-fuzzy technique for a copper tube. During the application of t...

2000
Ajith Abraham Baikunth Nath

In this paper, we present a neuro-fuzzy model for intelligent reactive power control and efficient utilization of power. The proposed neuro-fuzzy model will assist the conventional power control systems with added intelligence. For on-line control, voltage and current are fed into the network after preprocessing and standardization. The model was trained with a 24-hour load demand pattern and p...

Journal: :CoRR 2016
Zhengbing Hu Yevgeniy V. Bodyanskiy Oleksii K. Tyshchenko Olena O. Boiko

A new approach to data stream clustering with the help of an ensemble of adaptive neuro-fuzzy systems is proposed. The proposed ensemble is formed with adaptive neuro-fuzzy self-organizing Kohonen maps in a parallel processing mode. Their learning procedure is carried out with different parameters that define a nature of cluster borders’ blurriness. Clusters’ quality is estimated in an online m...

2007
ANKUR KUMAR

The paper proposed the adaptive noise suppression technique for suppression of noise in voice communication. There are different techniques earlier used for adaptive filteration like least mean square, kalman’s filter etc.In the paper we used “fuzzy logic” technique for adaptive filteration. We know about the theory of adptive filteration of noise and application of fuzzy logic. We are using th...

2014
Nidhi Arora

----------------------------------------------------------------------ABSTRACT-------------------------------------------------------------Traditional algorithmic approaches are not suitable for solving today’s business problems. Neuro-Fuzzy systems have recently become popular and promising choice among researchers in attempt to solve complex problems faced in business. The paper presents a br...

2013
Narissara Eiamkanitchat

This research applies a Neuro-fuzzy method for clustering greenhouse gases produced by student activities. The partitional clustering algorithm is combined with Neuro-fuzzy. A standard dataset including iris and breast cancer is used to test the ability of the clustering algorithm. All activities who live in university dormitories are used to calculate the coefficient greenhouse gas emissions. ...

2006
Romeo Mark A. Mateo Malrey Lee Su-Chong Joo Jaewan Lee

Data mining tools generally deal with highly structured and precise data. However, classical methods fail to handle imprecise or uncertain information. This paper proposes a neuro-fuzzy data mining approach which provides a means to deal with the uncertainty of data. This presents a location-based service collaboration framework and uses the neuro-fuzzy algorithm for data mining. It also introd...

2012
Suriti Gupta Vinod Kumar B. Chen Y. Zhang J. Yen

In this paper, a neuro-fuzzy based Call Admission Control (CAC) algorithm for ATM networks has been simulated. The algorithm presented employs neuro-fuzzy approach to calculate the bandwidth require to support multimedia traffic with QoS requirements. The neuro-fuzzy based CAC calculates bandwidth required per call using measurements of the traffic via its count-process, instead of relying on s...

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  • "; pgn_html+=pgn_li; } document.getElementById("pgn-ul").innerHTML=pgn_html var pgn_links = document.querySelectorAll('.mypgn'); pgn_links.forEach(function(pgn_link) { pgn_link.addEventListener('click', paginate) }) } function post_and_fetch(data,url) { showLoading() xhr = new XMLHttpRequest(); xhr.open('POST', url, true); xhr.setRequestHeader('Content-Type', 'application/json; charset=UTF-8'); xhr.onreadystatechange = function() { if (xhr.readyState === 4 && xhr.status === 200) { var resp = xhr.responseText; resp_json=JSON.parse(resp) resp_place = document.getElementById("search_result_div") resp_place.innerHTML = resp_json['results'] search_meta = resp_json['meta'] update_search_meta(search_meta) update_pagination() hideLoading() } }; xhr.send(JSON.stringify(data)); } function unfilter() { url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":"unfilter", "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } function deactivate_all_bars(){ var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(bar) { bar.dataset.active = false bar.style = "stroke:#71a3c5;" }) } year_chart.on("created", function() { var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(check) { check.addEventListener('click', checkIndex); }) }); function checkIndex(event) { var yrchart = document.querySelectorAll('.ct-bar'); var year_bar = event.target if (year_bar.dataset.active == "true") { unfilter_res = unfilter() year_bar.dataset.active = false year_bar.style = "stroke:#1d2b3699;" } else { deactivate_all_bars() year_bar.dataset.active = true year_bar.style = "stroke:#e56f6f;" filter_year = chart_data['labels'][Array.from(yrchart).indexOf(year_bar)] url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":filter_year, "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } } function showLoading() { document.getElementById("loading").style.display = "block"; setTimeout(hideLoading, 10000); // 10 seconds } function hideLoading() { document.getElementById("loading").style.display = "none"; } -->