FUZZY MULTI-OBJECTIVE LINEAR PROGRAMMING APPROACH FOR SOLVING PROBLEM OF FOOD INDUSTRY

Enterprises and industrial centers need current decision for making products in fast changing market. Uncertainty and yield defined goals make decision making more difficult. In this situation fuzzy logic is used for coping surrounding environment. This paper deals with a fuzzy linear programming model for a problem of food industry. The different types of achievement function such as compensatory and weighted compensatory form&nbsp

APPLICATION OF INTELLIGENT GAME THEORY APPROACH IN COGNITIVE RADIO AD HOC NETWORKS

Cognitive Radio (CR) technology is imagined to solve the problems in Wireless Ad-hoc NETworks (WANET) resulting from the limited available spectrum and the inefficiency in the spectrum usage by exploiting the existing wireless spectrum opportunistically. Game theory is a process to analyze multi-person decision making situation, where each decision maker tries to maximize his own utility. In this paper, we illustrates how various interactions in Cognitive Radio Ad Hoc Network (CRAHN) can be modeled as a game. It also illustrates a problem with solution approach that uses intelligent game theory technique in CRAHN

MATHEMATICAL MODEL FOR INVENTORY CONTROL PROBLEM USING IMPRECISE PARAMETERS

In this paper, an inventory control problem is discussed using imprecise parameters. The fusion of geometric programming and fuzzy logic is used as imprecise parameters to solve inventory control problems. In inventory, holding costs, set-up costs, etc. may be flexible due to vague information. Fuzzy set theory is used to convert the inventory model crisp to fuzzy for producing flexible output. Compensatory operator is used to aggregate the fuzzy membership functions corresponding to fuzzy sets for fuzzy objectives and constraints. This aggregation gives the overall achievement function and the model known as fuzzy geometric programming model. &nbsp

OVERVIEW OF ELECTROMAGNETIC INTERFERENCE ISSUES IN AIRCRAFT

Purpose of Study: In the modern era, due to several conflictions or uncertainty in the aircraft, Electromagnetic Interference (EMI) or Radio Frequency Interference (RFI) issues occurred, frequently. The main reason behind it several disturbances generated by an external source that imitate wireless circuits with the help of conduction, electrostatic coupling, and electromagnetic induction. These disturbances may decrease the performance of the circuits or sometimes fully stop the operations. Methodology: The main challenges in EMI are modeling and simulation for modern and future wireless communication systems and networks taking into account nonlinear interference effects. Result: In this paper, overviews of several issues of EMI or RFI are illustrated

ON VARIOUS TECHNIQUES IN OFDM AND GFDM: A SURVEY

Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier modulation that divides the available spectrum into a finite number of carriers and applied into a digital transmission system. But it has some drawbacks such as sensitivity in inter-carrier interference, high peak to average power ratio and insufficient cyclic prefix in spectrum. These drawbacks may be reduced by a technique known as Generalized Frequency Division Multiplexing (GFDM). In the present scenario, it is a high speed multi-carrier multiplexing data transfer scheme for the cellular network. This paper deals with a comparison between OFDM and GFDM and focuses on various techniques in OFDM and GFDM

CORRELATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES WITH SOFT COMPUTING IN VARIOUS AREAS

Artificial Intelligence (AI) is a part of computer science concerned with designing intelligent computer systems that exhibit the characteristics used to associate with intelligence in human behavior. Basically, it define as a field that study and design of intelligent agents. Traditional AI approach deals with cognitive and biological models that imitate and describe human information processing skills. This processing skills help to perceive and interact with their environment. But in modern era developers can build system that assemble superior information processing needs of government and industry by choosing from large areas of mature technologies. Soft Computing (SC) is an added area of AI. It focused on the design of intelligent systems that process uncertain, imprecise and incomplete information. It applied in real world problems frequently to offer more robust, tractable and less costly solutions than those obtained by more conventional mathematical techniques. This paper reviews correlation of artificial intelligence techniques with soft computing in various areas

GFDM FOR NEXT GENERATION WIRELESS COMMUNICATION SYSTEM

In modern scenarios, there are several applications of OFDM, but it also has some demerits like sensitive to Carrier Frequency Offset (CFO), high Peak to Average Power Ratio (PAPR), and timing offset large. Out Of Band (OOB) and low spectral efficiency due to cyclic prefix per symbol insertion. To diminish and discard above problems, new multiplexing technique is required for next generation wireless communication i.e. GFDM. GFDM is becoming popular day by day due to flexibility in pulse shape as well as single cyclic prefix in a multipath channel and which makes it eligible for the 5th generation technology. This paper deals with an overview of a GFDM and presents a comparative study between OFDM and GFDM

APPLICATION OF SOFT COMPUTING TECHNIQUES OVER HARD COMPUTING TECHNIQUES: A SURVEY

Soft computing is the fusion of different constituent elements. The main aim of this fusion to solve real-world problems, which are not solve by traditional approach that is hard computing. Actually, in our daily life maximum problem having uncertainty and vagueness information. So hard computing fail to solve this problems, because it give exact solution. To overcome this situation soft computing techniques plays a vital role, because it has capability to deal with uncertainty and vagueness and produce approximate result. This paper focuses on application of soft computing techniques over hard computing techniques

An Energy Efficient and Cost Reduction based Hybridization Scheme for Mobile Ad-hoc Networks (MANET) over the Internet of Things (IoT)

Wireless networks are viewed as the best-used network and specifically Portable Specially Appointed Organizations (MANETs) have tracked down numerous applications for its information transmission progressively. The plan issues in this organization are to confine the utilization of energy while communicating data and give security to the hubs. Soa protocol needs to be energy efficient to avoid network failures. Thereby this paper brings an effective energy efficient to optimize LEAR and make it energy efficient. The energy-mindfulness element is added to the LEAR guiding convention in this work using the Binary Particle Swarm Optimization method (BPSO). The recommended method selects programmes taking into account course length in addition to the programme level of energy when predicting the future. To get good results, the steered challenge is first designed using LEAR. The next step is to choose a route that enhances the weighting capability of the study hours and programming power used.This MANET has been secured using the cryptographic method known as AES.According to experimental findings, the proposed hybrid version outperformed other cutting-edge models

A Neural Radiance Field-Based Architecture for Intelligent Multilayered View Synthesis

A mobile ad hoc network is made up of a number of wireless portable nodes that spontaneously come together en route for establish a transitory network with no need for any central management. A mobile ad hoc network (MANET) is made up of a sizable and reasonably dense community of mobile nodes that travel across any terrain and rely solely on wireless interfaces for communication, not on any well before centralized management. Furthermore, routing be supposed to offer a method for instantly delivering data across a network between any two nodes. Finding the best packet routing from across infrastructure is the major issue, though. The proposed protocol's major goal is to identify the least-expensive nominal capacity acquisition that assures the transportation of realistic transport that ensures its durability in the event of any node failure. This study suggests the Optimized Route Selection via Red Imported Fire Ants (RIFA) Strategy as a way to improve on-demand source routing systems. Predicting Route Failure and energy Utilization is used to pick the path during the routing phase. Proposed work assess the results of the comparisons based on performance parameters like as energy usage, packet delivery rate (PDR), and end-to-end (E2E) delay. The outcome demonstrates that the proposed strategy is preferable and increases network lifetime while lowering node energy consumption and typical E2E delay under the majority of network performance measures and factors