In the structure of ANFIS, there are two different parameter groups: premise and consequence. Training ANFIS means determination of these parameters using an optimization algorithm. In the first ANFIS model developed by Jang, a hybrid learning approach was proposed for training. In this approach, while premise parameters are determined by using gradient descent (GD), consequence parameters are found out with least squares estimation (LSE) method. Since ANFIS has been developed, it is used in modelling and identification of numerous systems and successful results have been achieved. The selection of optimization method utilized in training is very important to get effective results with ANFIS. It is seen that derivate based (GD, LSE etc.) and non-derivative based (heuristic algorithms such us GA, PSO, ABC etc.) algorithms are used in ANFIS training. Nevertheless, it has been observed that there is a trend toward heuristic based ANFIS training algorithms for better performance recently. At the same time, it seems to be proposed in derivative and heuristic based hybrid algorithms. Within the scope of this study, the heuristic and hybrid approaches utilized in ANFIS training are examined in order to guide researchers in their study. In addition, the final status in ANFIS training is evaluated and it is aimed to shed light on further studies related to ANFIS training.

Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey

Despite the extensive use of mortars materials in constructions over the last decades, there is not yet a reliable and robust method, available in the literature, which can estimate its strength based on its mix parameters. This limitation is due to the highly nonlinear relation between the mortar’s compressive strength and the mixed components. In this paper, the application of artificial intelligence techniques toward the prediction of the compressive strength of cement-based mortar materials with or without metakaolin has been investigated. Specifically, surrogate models (such as artificial neural network, ANN and adaptive neuro-fuzzy inference system, ANFIS models) have been developed to the prediction of the compressive strength of mortars trained using experimental data available in the literature. The comparison of the derived results with the experimental findings demonstrates the ability of both ANN and ANFIS models to approximate the compressive strength of mortars in a reliable and robust manner. Although ANFIS was able to obtain higher performance prediction to estimate the compressive strength of mortars compared to ANN model, it was found through the verification process of some other additional data, the ANFIS model has overfitted the data. Therefore, the developed ANN model has been introduced as the best predictive technique for solving problem of the compressive strength of mortars. Furthermore, using the optimum developed model an ambitious attempt to reveal the nature of mortar materials has been made.

A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength

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How the mobile communication

Neural network and multi-fractal dimension features for breast cancer classification from ultrasound images

Since the inception of IEEE 802.11 wireless local area networks (WLANs) in 1997, wireless networking technologies have tremendously grown in the last few decades. The fundamental IEEE 802.11 physical (PHY) and medium access control (MAC) protocols have continuously been enriched with new technologies to provide the last mile wireless broadband connectivity to end users. Consequently, several new amendments of the basic IEEE 802.11 gradually came up in the forms of IEEE 802.11a, IEEE 802.11b, and IEEE 802.11g. More recently, IEEE 802.11n, IEEE 802.11ac, and IEEE 802.11ad are introduced with enhanced PHY and MAC layers that boost up physical data rates to the order of Gigabit per second. So, these amendments are generally known as high throughput WLANs (HT-WLANs). In HT-WLANs, PHY layer is enhanced with multiple-input multiple-output antenna technologies, channel bonding, short guard intervals, enhanced modulation and coding schemes. The MAC sublayer overhead is reduced by introducing frame aggregation and block acknowledgement technologies. However, several existing studies reveal that, many a time, the aforesaid PHY and MAC enhancements yield negative impact on various upper layer protocols, that is end-to-end transport and application layer protocols. As a consequence, a large number of researchers have focused on improving the coordination among PHY/MAC and upper layer protocols. In this survey, we discuss impact of HT-WLAN PHY and MAC layer enhancements on various transport and application layer protocols. This paper also summarizes several research works that use aforesaid enhancements effectively to boost up data rate of end-to-end protocols. We also point out limitations of the existing researches and list down different open challenges that can be meaningfully explored for the development of the next generation HT-WLAN technologies.

Impact of IEEE 802.11n/ac PHY/MAC High Throughput Enhancements on Transport and Application Protocols—A Survey

Soft Computing is conglomerate of methodologies which works together and provides an ability to make a decision from reliable data or expert’s experience. Nowadays different types of soft computing techniques such as neural network, fuzzy logic, genetic algorithm and hybrid system are largely used in medical areas. In this paper, an algorithm for analysis of lung infection is presented. The main focus is to develop system architecture to find probable disease stage patient may have. Severity level of disease is determined by using rule base method. The algorithm uses an output of Rulebase entered by the user to determine a level of infection. Normal 0 false false false EN-MY X-NONE X-NONE /* Style Definitions */
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 Soft Computing is conglomerate of methodologies which works together and provides an ability to make decision from reliable data or expert’s experience. Nowadays different types of soft computing techniques such as neural network, fuzzy logic, genetic algorithm and hybrid system are largely used in medical areas. In this paper, algorithm for analysis of lung infection is presented. The main focus is to develop system architecture to find probable disease stage patient may have. Severity level of disease is determined by using rule base method. The algorithm uses output of Rulebase entered by user to determine level of infection.

https://ijai.iaescore.com/index.php/IJAI/article/download/1409/pdf

Effective Analysis of Lung Infection using Fuzzy Rules

Clustering is a key technique to improve the network lifetime, decrease the energy consumption and increase the scalability of the sensor network. In this paper, the different clustering algorithms for heterogeneous Wireless Sensor Networks (WSNs) are examined to study its performance with the impact of heterogeneity of the nodes. The main objective of this paper is to compare the different hierarchical routing protocol and propose an optimized algorithm for the clustering in order to prolong network lifetime. Prolonging network lifetime is the way to provide energy efficient WSNs.

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A Comparative Analysis of Hierarchical Routing Protocols in Wireless Sensor Networks

Erbium doped fiber amplifiers (EDFA) are most commonly used in optical networks for the most assorted applications. In this paper we have investigated the power transient effect of the cascaded erbium-doped fiber amplifiers (EDFA) in dense wavelength optical ring networks. The result shows, the power transient effect of EDFAs when channels are changed due to failure or channel reconfiguration. And also ring laser configuration technique has been reported to mitigate the effect of power transients.

https://eujournal.org/index.php/esj/article/download/2932/2761

OBSERVATION AND MITIGATION OF POWER TRANSIENTS IN 160Gbps OPTICAL BACKHAUL NETWORKS

Abstract This paper successfully demonstrates bidirectional wavelength division multiplexing passive optical network (WDM-PON) system for 32 channels, 0.8 nm (100 GHz) channels spacing with 3.5 GHz filter bandwidth. The system delivers 160 GB/s data rate and 80 GB/s data rate in downstream and upstream, respectively. The optical source for downstream data and upstream data is mode-locked laser at central office and reflective semiconductor optical amplifier (RSOA) at optical network unit. The maximum reach of designed system is 50 km without using any dispersion compensation scheme. This paper comprises comparison of series of modulation format in downstream and upstream such as SOLITON, NRZ, RZ, MANCHESTER, CSRZ and CRZ-DPSK and optimization of the performance of designed system. It has been observed that CRZ-DPSK/NRZ gives best performance in downstream and upstream transmission for designed system. The simulation work report of minimum BER is e−13 for CRZ-DPSK in downstream and e−16 for NRZ in upstream transmission in case of 32-channel bidirectional WDM-PON.

Performance Enhancement of Multichannel Gigabit Rate Bidirectional WDM-PON Using RSOA and Optimized Modulation Format

Optical Code Division Multiple Access (OCDMA) combines the large bandwidth of the fiber medium with the flexibility of the CDMA technique to achieve high speed connectivity. This paper presents the simulation module for OCDMA transmission and reception. The proposed network permits large number of users to communicate at high data rate. This paper describes a technology demonstrator for an incoherent optical code-division multi- ple-access scheme based on wavelength/time codes. The system supports 36 users operating at 10 Gsymbols/s/user while maintaining bit-error rate (BER) < 10-12 for the correctly decoded signal. Experiments support simulations which show that coherent beat noise, occurring between the signal and multiple access interference, ultimately limits system performance.

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Anurag Sharma

Papers

Effective Analysis of Lung Infection using Fuzzy Rules

A Comparative Analysis of Hierarchical Routing Protocols in Wireless Sensor Networks

OBSERVATION AND MITIGATION OF POWER TRANSIENTS IN 160Gbps OPTICAL BACKHAUL NETWORKS

Performance Enhancement of Multichannel Gigabit Rate Bidirectional WDM-PON Using RSOA and Optimized Modulation Format

Design and Performance investigation of multiuser OCDMA network