نتایج جستجو برای: cost function modelling

تعداد نتایج: 1704659  

Journal: :IOP Conference Series: Materials Science and Engineering 2021

Faramarz Sarhaddi Mohammad Mahdi Naserian Said Farahat

In this study, the performance of an irreversible regenerative Brayton cycle is sought through power maximizations using finite-time thermodynamic concept in finite-size components. Optimizations are performed using a genetic algorithm. In order to take into account the finite-time and finite-size concepts in the current problem, a dimensionless mass-flow rate parameter is used to deploy ti...

Journal: :CoRR 2015
Ilya Sutskever Rafal Józefowicz Karol Gregor Danilo Jimenez Rezende Timothy P. Lillicrap Oriol Vinyals

General unsupervised learning is a long-standing conceptual problem in machine learning. Supervised learning is successful because it can be solved by the minimization of the training error cost function. Unsupervised learning is not as successful, because the unsupervised objective may be unrelated to the supervised task of interest. For an example, density modelling and reconstruction have of...

2004
Günther A. Hoffmann Felix Salfner Miroslaw Malek

The availability of software systems can be increased by preventive measures which are triggered by failure prediction mechanisms. In this paper we present and evaluate two non-parametric techniques which model and predict the occurrence of failures as a function of discrete and continuous measurements of system variables. We employ two modelling approaches: an extended Markov chain model and a...

H. Nehzati, M. Esfahanian, M. Masih-Tehrani, M.J. Esfandiary, V. Esfahanian,

The Energy Storage System (ESS) is an expensive component of an E-bike. The idea of Hybrid Energy Storage System (HESS), a combination between battery and Ultra-Capacitor (UC), can moderate the cost of E-bike ESS. In this paper, a cost function is developed to use for optimal sizing of a HESS. This cost function is consisted of the HESS (battery, UC and DC/DC converter) cost and the cost of bat...

This paper applies an evolutionary algorithm, the particle swarm optimization (PSO), to design the optimum open channel section. Depth, channel side slope and bottom width are considered as the variables for rectangular, triangular and trapezoidal channels, respectively. The objective function is minimizing the construction cost of the channel section. MATLAB software is used for programming an...

2009
Maksym Polyakov David N. Wear Robert Huggett

Timber supply has traditionally been modelled using aggregate data. In this paper, we build aggregate supply models for four roundwood products for the US state of North Carolina from a stand-level harvest choice model applied to detailed forest inventory. The simulated elasticities of pulpwood supply are much lower than reported by previous studies. Cross price elasticities indicate a dominant...

Journal: :اقتصاد و توسعه کشاورزی 0
محمدرضا پاکروان امید گیلانپور شیرین ظریف

liberalization of energy price increases costs of agricultural inputs and costs of agricultural production. all these changes may affect the overall competitiveness of domestic products with similar foreign products. as a result of that, total cost of agricultural products are increased and profitability are decreased. in this paper, energy consumption for producing corn were calculated using c...

Journal: :Research Journal of Applied Sciences, Engineering and Technology 2015

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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"; } -->