نتایج جستجو برای: multi componential model

تعداد نتایج: 2455934  

Journal: :مدیریت زنجیره تأمین 0
مهدی سلطانی تهرانی مسعود مصدق خواه حسینعلی حسن پور

today, due to the direct and reverse logistics plays an important role in reducing the costs in supply chain. in this paper, in order to provide a closed-loop supply chain network including supply centers, production, distribution, collection, recycling and disposal of a used linear mixed integer programming. this paper to consider multi-period and multi-product in multi-level supply chain and ...

Journal: :بین المللی مهندسی صنایع و مدیریت تولید 0
zahra attaei ahmad makoui

this paper is a research on the ordering planning of a supply chain with one supplier, multi buyer and multi deteriorating items. items have fixed life time and expire dates. the ordering period is taken as variable and must be computed the proposed models. the problem is studied via two different approaches the first is the joint replenishment, based on the hwang and chew's model [3] and ...

Journal: :journal of computer and robotics 0
seyed mahmood hashemi school of computer engineering, darolfonoon high educational institute, qazvin, iran

fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. in this research, fcm is chosen for fuzzy clustering. parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. these two parameters require tuning to reduce the overfitting in the...

Journal: :journal of advances in computer research 0
hasan nasiri soloklo department of electrical engineering, firoozkooh branch, islamic azad university, firoozkooh, iran malihe maghfoori farsangi electrical engineering department, shahid bahonar university of kerman, kerman, iran

in this paper, a new alternative method for order reduction of high order systems is presented based on optimization of multi objective fitness function by using harmony search algorithm. at first, step response of full order system is obtained as a vector, then, a suitable fixed structure considered for model order reduction which order of original system is bigger than fixed structure model. ...

2014
Alastair C. Smith Padraic Monaghan Falk Huettig

The effect of literacy on phonological processing has been described in terms of a virus that “infects all speech processing” (Frith, 1998). Empirical data has established that literacy leads to changes to the way in which phonological information is processed. Harm & Seidenberg (1999) demonstrated that a connectionist network trained to map between English orthographic and phonological represe...

2006
Gerard Steen

1. From Structuralist Semantics to Cognitive Linguistics When Roman Jakobson pulled metaphor and metonymy to the center of the stage in linguistics and poetics, structuralists were trying to account for meaning by means of a componential model of clearly defined semantic elements (Jakobson, "Closing Statement"). Inspired by the success of Vladimir Propp's structuralist narratology, which attemp...

2013
Woojae Kim Mark A. Pitt Jay I. Myung

Parallel Distributed Processing (PDP) models have had a profound impact on the study of cognition. One domain in which they have been particularly influential is quasiregular learning, in which mastery requires both learning regularities that capture the majority of the structure in the input plus learning exceptions that violate the regularities. How PDP models learn quasiregularity is still n...

Journal: :Consciousness and cognition 2008
Didier Grandjean David Sander Klaus R Scherer

In this paper we discuss the issue of the processes potentially underlying the emergence of emotional consciousness in the light of theoretical considerations and empirical evidence. First, we argue that componential emotion models, and specifically the Component Process Model (CPM), may be better able to account for the emergence of feelings than basic emotion or dimensional models. Second, we...

This article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (MPC) of a chemical plant. A combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (MIMO) process with time delays.  An optimization procedure for a neural MPC algorithm based on this model is then developed. T...

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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="
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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"; } -->