نتایج جستجو برای: artificial neural network firefly algorithm

تعداد نتایج: 1640338  

Journal: :iranian journal of medical physics 0
javad haddadnia biomedical engineering department, hakim sabzevari university, center for research of advanced medical technologies, sabzevar university of medical sciences, sbzevar, iran

introduction this study is an effort to diagnose breast cancer by processing the quantitative and qualitative information obtained from medical infrared imaging. the medical infrared imaging is free from any harmful radiation and it is one of the best advantages of the proposed method. by analyzing this information, the best diagnostic parameters among the available parameters are selected and ...

Introduction: cardiovascular diseases are becoming the main cause of mortality and morbidity in most countries. This research goal was to predict the types of heart diseases for more accurate diagnosis by data mining and neural network technics. Method: This research was an applied-survey study and after data preprocessing, three approaches of neural network, decision making tree and Bayes simp...

Journal: :civil engineering infrastructures journal 0
fatemeh barzegari instructor of agricultural department, payam noor university, iran. mohsen yousefi m.sc., faculty of natural resources, yazd university, iran ali talebi associate professor, faculty of natural resources, yazd university, iran.

the aim of this study was to estimate suspended sediment by the ann model, dt with cart algorithm and different types of src, in ten stations from the lorestan province of iran. the results showed that the accuracy of ann with levenberg-marquardt back propagation algorithm is more than the two other models, especially in high discharges. comparison of different intervals in models showed that r...

Introduction: cardiovascular diseases are becoming the main cause of mortality and morbidity in most countries. This research goal was to predict the types of heart diseases for more accurate diagnosis by data mining and neural network technics. Method: This research was an applied-survey study and after data preprocessing, three approaches of neural network, decision making tree and Bayes simp...

Journal: :international journal of hematology-oncology and stem cell research 0
mehrdad payandeh hematology-oncology department, faculty of medical science, kermanshah university of medical science,kermanshah, iran mehrnoush aeinfar hematology-oncology department, faculty of medical science, kermanshah university of medical science, kermanshah, iran vahid aeinfar electronic department, faculty of technology, razi university, kermanshah, iran computational intelligence research center, razi university, kermanshah, iran mohsen hayati electronic department, faculty of technology, razi university, kermanshah, iran computational intelligence research center, razi university, kermanshah, iran

abstract: this paper represents a novel use of artificial neural networks in medical science. the proposed technique involves training a multi layer perceptron (mlp) (a kind of artificial neural network) with a bp learning algorithm to recognize a pattern for the diagnosing and prediction of five blood disorders, through the results of blood tests from h1 machine. the blood test parameters and ...

Journal: :iranian journal of chemistry and chemical engineering (ijcce) 2010
najeh alali mahmoud reza pishvaie vahid taghikhani

production of highly viscous tar sand bitumen using steam assisted gravity drainage (sagd) with a pair of horizontal wells has advantages over conventional steam flooding. this paper explores the use of artificial neural networks (anns) as an alternative to the traditional sagd simulation approach. feed forward, multi-layered neural network meta-models are trained through the back-error-propaga...

Journal: :journal of advances in computer research 2014
elham imaie abdolreza sheikholeslami roya ahmadi ahangar

according to this fact that wind is now a part of global energy portfolio and due to unreliable and discontinuous production of wind energy; prediction of wind power value is proposed as a main necessity. in recent years, various methods have been proposed for wind power prediction. in this paper the prediction structure involves feature selection and use of artificial neural network (ann). in ...

Journal: :nutrition and food sciences research 0
hajar abbasi islamic azad university, esfahan branch (khorasgan), arghavanieh, jey st., esfahan, iran. post code: 81551-39998, p.o.box: 81595-158 seyyed mahdi seyedain ardabili department of food science and technology, faculty of agriculture and natural resources, science and research branch, islamic azad university, tehran, iran mohammad amin mohammadifar department of food science and technology, faculty of nutrition sciences, food science and technology / national nutrition and food technology research institute, shahid beheshti university of medical sciences, po box 19395-47471, tehran, iran zahra emam-djomeh transfer phenomena laboratory, department of food science, technology and engineering, faculty of agricultural engineering and technology, agricultural campus of the university of tehran, po box 4111, 31587-11167 karadj, iran

background and objectives: rheological characteristics of dough are important for achieving useful information about raw-material quality, dough behavior during mechanical handling, and textural characteristics of products. our purpose in the present research is to apply soft computation tools for predicting the rheological properties of dough out of simple measurable factors. materials and met...

Journal: :journal of ai and data mining 2014
mohaddeseh dashti vali derhami esfandiar ekhtiyari

yarn tenacity is one of the most important properties in yarn production. this paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. the artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 ne. as the first step for modeling, the empirical data is col...

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