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Open Banking Innovation Model by Digital Transformations Based on Adaptive neuro fuzzy inference System (ANFIS)

کلیدواژه: Digital Transformation,Open Banking,Banking Innovation,Business Strategy,Business Model

نویسندگان: Mirfallah Lialestani Mohammadali, KHAMSEH ABBAS

ناشر: JOURNAL OF SYSTEM MANAGEMENT - JOURNAL OF SYSTEM MANAGEMENT

Given the emergence of digital transformation from Industry 4 and the rapid dissemination of technological innovations as well as their impact as a strong driving force in new banking businesses, efforts should be made to identify the dimensions of this core factor as rapidly as possible. Providing ... ادامه

سال:2021

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Long-Term Rainfall Estimation in Anzali City Using the Hybrid Wavelet-Adaptive neuro-fuzzy inference System Model

کلیدواژه: Rainfall,ANFIS,Wavelet,Sensitivity analysis,Simulation,Anzali city

نویسندگان: PASANDIDEH IRAJ, IZADBAKHSH MOHAMMAD ALI, SHABANLOU SAEID

ناشر: تحقیقات آب و خاک ایران - Iranian Journal of Soil and Water Research

Recently, the amount of rainfall underwent serious changes in different areas, particularly in arid and semi-arid regions. Therefore, estimation and pattern recognition of rainfall in a long term period can give sufficient information to hydrologists and water engineers. In this study, for the first... ادامه

سال:2019

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Predicting Unconfined compressive Strength of Intact Rock Using New Hybrid Intelligent Models

کلیدواژه: Intact rock,Unconfined compressive strength,Adaptive neuro-fuzzy inference system,Genetic algorithm,Particle swarm optimization

نویسندگان: REZAEI M., Asadizadeh M.

ناشر: معدن و محیط زیست - JOURNAL OF MINING AND ENVIRONMENTAL (INTERNATIONAL JOURNAL OF MINING & ENVIRONMENTAL ISSUES)

Bedrock unconfined compressive strength (UCS) is a key parameter in designing the geosciences and building related projects comprising both the underground and surface rock structures. Determination of rock UCS using standard laboratory tests is a complicated, expensive, and time-consuming process, ... ادامه

سال:2020

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Evaluation of the Accuracy of Wavelet-neuro-fuzzy, neuro-fuzzy, and Wavelet Hybrid Models in Groundwater Level Prediction (Case Study: Birjand Plain)

کلیدواژه: Wavelet analysis, Groundwater Level, Birjand plain, Fuzzy Neural Network, Water resources management

نویسندگان: Dastuorani Mehdi, Khayat Amir, Akhondi Zahra

ناشر: آبخوان و قنات - Journal of Aquifer and Qanat

Given the scarcity of water resources and the importance of their optimal management, accurate prediction of groundwater level fluctuations is essential. Intelligent models such as time series, wavelet analysis, artificial neural networks, and support vector machines can help in the sustainable u... ادامه

سال:2024

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optimization of Hyperparameters in Hybrid Deep Learning Models for Sleep Apnea Detection Using swarm Intelligence Algorithms

کلیدواژه: Sleep Apnea, HoneyBadger Optimizer, GreyWolf Optimizer, Convolutional neural network, Deep Recurrent Neural Network

نویسندگان: Fotouhi-Ghazvini Faranak, Badiee Maryam

ناشر: پژوهش های نظری و کاربردی هوش ماشینی - Journal of Applied and Basic Machine Intelligence Research

This study investigates the efficiency of CNN-DRNN hybrid classifiers in detecting sleep apnea using electrocardiogram (ECG) signals. Various CNN models were evaluated, including AlexNet, VGG16, VGG19, and ZFNet, along with DRNN models such as LSTM, GRU, and BiLSTM. These models were compared with a... ادامه

سال:2025

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Using Hybrid Model of Particle swarm optimization and Multi-Layer Perceptron Neural Networks for Classification of Diabete

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ناشر: International Journal of Intelligent Engineering and Systems - International Journal of Intelligent Engineering and Systems

... ادامه

سال:2021

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Intelligent Modeling; Single (Multi-layer perceptron) and Hybrid (neuro-fuzzy Network) Method in Forest Degradation (Case Study: Sari County)

کلیدواژه: Intelligent Modeling,Multilayer Perceptron,Neural-Fuzzy,Forest Degradation

نویسندگان: Mehrabadi Somayeh

ناشر: تحقیقات کاربردی علوم جغرافیایی - Journal of Applied Researches in Geographical Sciences

The classical methods, also known as hard methods, are based on the accuracy of calculations, while the real world is founded on the inaccuracy of boundaries and the uncertainties, which is more consistent with soft computing methods. Each of these methods has its own strengths and weaknesses, and t... ادامه

سال:2021

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The Application of Metaheuristic optimization Algorithms of Gravitational Search, Particle swarm, and their Hybrid in Fracture Network Modeling

کلیدواژه: Fractured Network Modeling,Multivariate Optimization Algorithms Particle Swarm Optimization,Gravitational Search Algorithm

نویسندگان: SHAKIBA Sima, DOULATI ARDEJANI FARAMARZ

ناشر: پژوهش نفت - PETROLEUM RESEARCH

Fractured network modeling is the main prerequisite for fluid flow simulation in many applications such as groundwater resource management, oil and gas reservoir simulation, geothermal energy resource modeling and etc. The aim of this study is to develop an iterative object-based algorithm for fract... ادامه

سال:2023

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Evaluation of the neuro-fuzzy and Hybrid Wavelet-Neural Models Efficiency in River Flow Forecasting (Case Study: Mohmmad Abad Watershed)

کلیدواژه: Daily flow time series,Flow forecasting,Neuro-fuzzy model,Wavelet-neural model

نویسندگان: Niromandfard Fariba, KHASHEI SIUKI ABBAS, SHAHIDI ALI

ناشر: پژوهشنامه مدیریت حوزه آبخیز - Journal of Watershed Management Research

One of the most important issues in watersheds management is rainfall-runoff hydrological process forecasting. Using new models in this field can contribute to proper management and planning. In addition, river flow forecasting, especially in flood conditions, will allow authorities to reduce the ri... ادامه

سال:2019

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Non– Intrusive Appliance Load Disaggregation in Smart Homes Using Hybrid Constrained Particle swarm optimization and Factorial Hidden Markov Model

کلیدواژه: Non–,Intrusive Appliance Load Disaggregation,Smart Home,Swarm Particle Optimization,Factorial Hidden Markov Model

نویسندگان: DEJAMKHOOY ABDOLMAJID, AHMADPOUR ALI, POURJAFAR SAEED

ناشر: JOURNAL OF ENERGY MANAGEMENT AND TECHNOLOGY - JOURNAL OF ENERGY MANAGEMENT AND TECHNOLOGY

Nowadays, the prediction of the load performances in the smart systems is necessary to generate the minimum energy. In a smart home, there are various appliances that each of them has different behavior. These differences defined as appliance states. In this paper, an effective hybrid method is prop... ادامه

سال:2019

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