Pemodelan Sistem Fuzzy dengan Menggunakan Matlab

Fuzzy logic is a method in soft computing category, a method that could process uncertain, inaccurate, and less cost implemented data. Some methods in soft computing category besides fuzzy logic are artificial network nerve, probabilistic reasoning, and evolutionary computing. Fuzzy logic has the ability to develop fuzzy system that is intelligent system in uncertain environment. Some stages in fuzzy system formation process is input and output analysis, determining input and output variable, defining each fuzzy set member function, determining rules based on experience or knowledge of an expert in his field, and implementing fuzzy system. Overall, fuzzy logic uses simple mathematical concept, understandable, detectable uncertain and accurate data. Fuzzy system could create and apply expert experiences directly without exercise process and effort to decode the knowledge into a computer until becoming a modeling system that could be relied on decision making

Implementasi Jaringan Syaraf Tiruan Recurrent dengan Metode Pembelajaran Gradient Descent Adaptive Learning Rate untuk Pendugaan Curah Hujan Berdasarkan Peubah Enso

The use of technology of technology Artificial Neural Network (ANN) in prediction of rainfall can be done using the learning approach. ANN prediction accuracy measured by the coefficient of determination (R2) and Root Mean Square Error (RMSE).This research employ a recurrent optimized heuristic Artificial Neural Network (ANN) Recurrent Elman gradient descent adaptive learning rate approach using El-Nino Southern Oscilation (ENSO) variable, namely Wind, Southern Oscillation Index (SOI), Sea Surface Temperatur (SST) dan Outgoing Long Wave Radiation (OLR) to forecast regional monthly rainfall. The patterns of input data affect the performance of Recurrent Elman neural network in estimation process. The first data group that is 75% training data and 25% testing data produce the maximum R2 69.2% at leap 0 while the second data group that is 50% training data & 50% testing data produce the maximum R2 53.6%.at leap 0 Our result on leap 0 is better than leap 1,2 or 3

Sistema de produção de leite em Rondônia: produção, reprodução, nutrição e alimentação.

Esta publicação apresenta um estudo sobre a produção leiteira no Estado de RO e propõe ações otimizadoras da produção.bitstream/item/24795/1/rt91-sistemadeproducaodeleite.pd

Program Aplikasi Steganografi Menggunakan Metode Spread Spectrum pada Perangkat Mobile Berbasis Android

The exchange of traffic information in cyberspace grows fast. In all areas of life utilize technology to exchange information. One of the media owned by many people is mobile device such as mobile phone and tablet computer. In fact many people have been using mobile devices for information exchange function, and expect information to be transmitted quickly, accurately, and safely. The information security sent will be very important when the information is confidential. One way to secure information sent is the concealment of information into a media so that information hidden is beyond recognition by the human senses, which is commonly referred to steganography. This research studied and implemented steganography using spread spectrum Method on Android-based mobile devices. The results showed that the inserted image before and after the message was inserted is not different with PSNR value of about 75

Effect of tail docking in Awassi lambs on metabolizable energy requirements and chemical composition of carcasses

The effect of tail docking on metabolizable energy requirements and carcass characteristics was studied using 80 weaned entire Awassi male lambs. Docking was performed within 3 days of birth and lambs were weaned at 90 days old. Docked and undocked lambs were randomly allocated to four groups, individually penned and offered different amounts of a pelleted concentrate diet. The pelleted diet was estimated to contain 11.8 MJ of metabolizable energy (ME) and 182 g of crude protein (CP) per kg dry matter (DM). Lambs on the high levels of intake were slaughtered at a target weight of approximately 45 kg. Other lambs were maintained on the diet for 149 days before being slaughtered. The right sides of all carcasses were cut into standardized commercial cuts then dissected into muscle, fat and bone. The soft tissue was pooled and analysed for DM, CP, ash and fat. Prediction of live-weight gain (LWG) and empty body gain for a given ME intake (MEI) was made using the growth and MEI data. MEI was expressed as MJ per kg metabolic body weight (M 0.75) per day. Tail docking had no effect (P> 0.05) on lamb growth from birth to weaning. During the post-weaning growth period, LWG and empty body gain were significantly higher (P 0.05) at high levels of intakes (between 0.74 and 1.1 MJ/kg M 0.75 per day). Hot and cold carcass weights were similar (P > 0.05) for the two groups. Differences in empty body weight and fleece-free empty body weight were significant (P 0.05) on food conversion efficiency (FCE). Carcasses from docked lambs had significantly lower (P 0.05) ash content

Epidemiological features of aplastic anaemia in Pakistan

Objective: To complete the data on the demographic features of patients diagnosed to have aplastic anemia at a single institution over a 7.5 years period. Methods: Demographic information was retrieved from the patients medical records retrospectively as well as prospectively of those patients who presented with features of aplastic anaemia. Their diagnosis was confirmed by performing a complete blood count and bone marrow trephine. Results: One hundred and forty four patients were diagnosed to have aplastic anemia; there were 106 males and 38 females. Their ages ranged from 2 to 75 years, with a median of 17 years, 112 (77.7%) patients were below the age of 30 years. Severe aplastic anemia (SAA) was seen in 74 (51.4%), very severe (VSAA) in 24 (16.7%) and non-severe aplastic anemia (NSAA) in 46(31.9%) patients. No obvious cause could be established for 74.3%. Thirteen patients admitted using drugs known to cause AA and one was a radiographer (9%). Out of 44 patients tested, 7 (15.9%) were found to have either hepatitis B virus markers or antibody to hepatitis C at the time of diagnosis of AA. However it was difficult to establish a cause and effect relationship with either drugs or viruses. Conclusion: Aplastic anaemia is found to occur mostly severe aplastic anaemia (JPMA 51:443,2001)

Implementasi Jaringan Syaraf Tiruan Recurrent Dengan Metode Pembelajaran Gradient Descent Adaptive Learning Rate Untuk Pendugaan Curah Hujan

Penggunaan teknologi di bidang Artificial Intellegence khususnya teknologi Jaringan Syaraf Tiruan (JST) dalampendugaan curah hujan dapat dilakukan dengan metoda pendekatan pembelajaran. Berdasarkan kemampuanbelajar yang dimilikinya, maka JST dapat dilatih untuk mempelajari dan menganalisa pola data masa lalu danberusaha mencari suatu formula atau fungsi yang akan menghubungkan pola data masa lalu dengan keluaranyang diinginkan pada saat ini. Keakuratan hasil prediksi JST diukur berdasarkan koefisien determinasi (R2) danRoot Mean Square Error (RMSE).Penelitian ini menerapkan jaringan syaraf tiruan Recurrent Elman yang teroptimasi secara heuristik untukpendugaan curah hujan berdasarkan peubah El-Nino Southern Oscilation (ENSO) seperti Angin, , SouthernOscillation Index (SOI), Sea Surface Temperatur (SST) dan Outgoing Long Wave Radiation (OLR) dengan studikasus daerah Bongan Bali.Optimasi pembelajaran heuristik yang dilakukan pada dasarnya adalah pengembangan kinerja algoritmapembelajaran gradient descent standard menjadi algoritma pelatihan yaitu : gradient descent adaptive learningrate. Pola input data yang digunakan sangat berpengaruh terhadap kinerja JST Recurrent Elman dalammelakukan proses pendugaan. Kelompok data pertama yaitu 75% data pelatihan & 25% data uji menghasilkanR2 maksimum 69,2% untuk leap 0 sedangkan kelompok data kedua yaitu 50% data pelatihan & 50% data ujimenghasilkan R2 maksimum 53,6 % untuk leap 0. Hasil nilai R2 pada leap 0 lebih baik dibandingkan pada leapl, leap 2 dan leap 3

Nonparametric Reconstruction of the Dark Energy Equation of State

A basic aim of ongoing and upcoming cosmological surveys is to unravel the mystery of dark energy. In the absence of a compelling theory to test, a natural approach is to better characterize the properties of dark energy in search of clues that can lead to a more fundamental understanding. One way to view this characterization is the improved determination of the redshift-dependence of the dark energy equation of state parameter, w(z). To do this requires a robust and bias-free method for reconstructing w(z) from data that does not rely on restrictive expansion schemes or assumed functional forms for w(z). We present a new nonparametric reconstruction method that solves for w(z) as a statistical inverse problem, based on a Gaussian Process representation. This method reliably captures nontrivial behavior of w(z) and provides controlled error bounds. We demonstrate the power of the method on different sets of simulated supernova data; the approach can be easily extended to include diverse cosmological probes.Comment: 16 pages, 11 figures, accepted for publication in Physical Review