نتایج جستجو برای: fi refly algorithm

تعداد نتایج: 778487  

2010
Kevin Zatloukal

fi(xi, xi−1, . . . , x1), for i = 1, . . . , n, where fi’s are from a fixed set Ops. – Most importantly, only xi is explicitly passed to the i-th function. The algorithm must store x1, . . . , xi−1 (or some functions thereof) in memory so it can access them when computing fi. – The idea is to arrange the values in some clever way (the data structure) in order to make computing the fi (and updat...

2009
Rhonda VanDyke Kert Viele Robin Cooper

A shape invariant model for functions f1, . . . , fn specifies that each individual function fi can be related to a common shape function g through the relation fi(x) = aig(cix + di) + bi. We consider a mixture model that allows multiple shape functions g1, . . . , gK , where each fi is a shape invariant transformation of one of those gk. We derive an MCMC algorithm for fitting the model using ...

Journal: :Information Fusion 2010
Pilar Bulacio Serge Guillaume Elizabeth Tapia Luis Magdalena

We consider the problem of collective decision-making from an arbitrary set of classifiers under Sugeno fuzzy integral (S-FI). We assume that classifiers are given, i.e., they cannot be modified towards their effective combination. Under this baseline, we propose a selection-combination strategy, which separates the whole process into two stages: the classifiers selection, to discover a subset ...

2005
G. Boccignone P. Napoletano

Diffused Expectation Maximisation (DEM) is a novel algorithm for image segmentation. The method models an image as a finite mixture, where each mixture component corresponds to a region class and uses a maximum likelihood approach to estimate the parameters of each class, via the expectation maximisation (EM) algorithm, coupled with anisotropic diffusion on classes, in order to account for the ...

Journal: :International Journal of Intelligent Computing Research 2012

Journal: :IAES International Journal of Artificial Intelligence 2023

<span lang="EN-GB">The recent trend in location-based services has led to a proliferation of studies indoor positioning technology. Wi-Fi</span><span lang="VI"> received signal strength </span><span lang="EN-US">indicator</span><span (RSSI) lang="EN-GB">Fingerprinting and pedestrian dead reckoning (PDR) are the two best representatives from both approac...

هدف این مقاله افزایش انعطاف پذیری مدل سازی نوسانات بازار سرمایه می باشد. این امربا معرفی مدل MRS-FI-TGARCH برای اولین بار در دنیا انجام می گیرد. به این منظور از شاخص هفتگی قیمت بورس اوراق بهادار تهران طی سالهای ۲۰۰۹ تا ۲۰۱۷ استفاده می شود .پارامترها قابلیت تغییر با رژیم را دارند. نتایج نشان داد دو رژیم رونق، با بازده انتظاری بالا و نوسان بالا و رژیم رکود، با بازده انتظاری پایین و نوسان پایینوجو...

Journal: :Information Management and Computer Science 2020

Journal: :Applied sciences 2022

Owing to the heterogeneity of software and hardware in different types mobile terminals, received signal strength indication (RSSI) from same Wi-Fi access point (AP) varies indoor environments, which can affect positioning accuracy fingerprint methods. To solve this problem consider nonlinear characteristics propagation attenuation, we propose a whale optimisation algorithm-back-propagation neu...

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function paginate(evt) { url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term pg=parseInt(evt.target.text) var data={ "year":filter_year, "term":term, "pgn":pg } filtered_res=post_and_fetch(data,url) window.scrollTo(0,0); } function update_search_meta(search_meta) { meta_place=document.getElementById("search_meta_data") term=search_meta.term active_pgn=search_meta.pgn num_res=search_meta.num_res num_pages=search_meta.num_pages year=search_meta.year meta_place.dataset.term=term meta_place.dataset.page=active_pgn meta_place.dataset.num_res=num_res meta_place.dataset.num_pages=num_pages meta_place.dataset.year=year document.getElementById("num_result_place").innerHTML=num_res if (year !== "unfilter"){ document.getElementById("year_filter_label").style="display:inline;" document.getElementById("year_filter_place").innerHTML=year }else { document.getElementById("year_filter_label").style="display:none;" document.getElementById("year_filter_place").innerHTML="" } } function update_pagination() { search_meta_place=document.getElementById('search_meta_data') num_pages=search_meta_place.dataset.num_pages; active_pgn=parseInt(search_meta_place.dataset.page); document.getElementById("pgn-ul").innerHTML=""; pgn_html=""; for (i = 1; i <= num_pages; i++){ if (i===active_pgn){ actv="active" }else {actv=""} pgn_li="
  • " +i+ "
  • "; 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"; } -->