The article presents the top soft computing applications that businesses should check out in 2023
Soft computing is the use of approximate calculations to provide imprecise but usable explanations for complex computational problems. Top soft computing applications enable solutions for problems that may be either unsolvable or just too time-consuming to solve with current hardware. soft computing applications are generally based on computational intelligence. Soft computing applications provide an approach to problem-solving using means other than computers. With the human mind as a role model, soft computing is tolerant of partial truths, uncertainty, imprecision, and approximation, unlike traditional computing models. The tolerance of soft computing enables researchers to deal with some serious problems that traditional computing can’t process. Companies are using soft computing applications to make them a step ahead in the competition. Therefore, Knowing the top soft computing applications for 2023 can provide a boost to one’s professional career. Here the article enlists the top 10 soft computing applications that Businesses should know in 2023.
Soft Computing in Investment and Trading
The data present in the finance field is grandiosity and traditional computing is unable to handle and process such kind of data. There are multiple soft computing techniques that help to handle those massive data. The pattern recognition approach is used to understand the pattern or behavior of the data and time series is used to predict future trading points.
Soft Computing Techniques in Bioinformatics
Soft computing applications in bioinformatics help to modify any uncertainty and indifference that biometrics data may have. Soft computing applications provide distinct low-cost solutions with the help of algorithms, databases, Fuzzy Sets (FSs), and Artificial Neural Networks (ANNs). These techniques are fantastic to deliver quality results in an efficient way.
Soft Computing based Architecture
In this process, an intelligent building gathers inputs from the sensors and controls effectors by using them. The construction industry uses the technique of DAI (Distributed Artificial Intelligence) and fuzzy genetic agents to deliver the building with capabilities that match human intelligence. The fuzzy logic of Soft Computing is used to create behavior-based architecture in intelligent buildings to deal with the unpredictable nature of the environment, and these agents embed sensory information in the buildings.
Soft Computing Techniques in Power System Analysis
Soft computing uses the method of Artificial Neural Networks to predict any instability in the voltage of the power system. Using the Artificial Neural Network, the pending voltage instability can be predicted. The methods which are deployed here, are very low in cost.
Soft Computing and Decision Support System
Top soft computing applications give the advantage of minimizing the cost of the decision support system. The methods are used to design, maintain, and maximize the value of the decision process. The first application of fuzzy logic is to create a decision system that can predict any sort of risk. The second application is using fuzzy information that selects the areas which need replacement.
Handwritten Script Recognition using Soft Computing
Handwritten Script Recognition is one of the most demanding parts of computer science. It has the ability to translate multilingual documents and sort the various scripts accordingly. It applies the concept of the “block-level technique” where the system recognizes the particular script from a number of script documents given. It uses a Discrete Cosine Transform (DCT), and discrete wavelets Transform (DWT) together, which classify the scripts according to their features.
Use of Soft Computing in Automotive Systems and Manufacturing
Soft computing applications have solved a major misconception about the automobile industry that it is slow to adapt. Fuzzy logic is a soft computing technique used in vehicles to develop classic control methods. It takes the example of human behavior, which is described in the form of rule – “If-Then “statements. The logic controller then converts the sensor inputs into fuzzy variables that are then defined according to these rules. Fuzzy logic has a crucial role in engine control, automatic transmissions, antiskid steering, etc.
Image Processing and Data Compression using Soft Computing
Image analysis is one of the crucial parts of the medical field. It uses a high-level processing technique that includes recognition and bifurcation of patterns. Using soft computing solves the problem of computational complexity and efficiency in classification. Soft computing techniques including Genetic Algorithms, Genetic Programming, Classifier Systems, Evolution Strategies, artificial life, and a few others are used to deliver the best result.
Soft Computing Applications in Supply Chain Management
It is clear that effective supply chain management (SCM) is imperative in order for organizations to compete and have a strategic competitive advantage. Multiple soft computing (SC) techniques including but not limited to fuzzy logic and fuzzy sets, artificial neural networks, genetic algorithms, Bayesian networks, rough set theory, etc have been applied for decision-making and analysis within a number of supply chain management processes.
Application of Soft Computing Techniques for Renewable Energy Network Design and Optimization
Energy operation can be characterized by its complex network system composed of energy generation, energy transformation, energy transportation, and energy consumption. The applications of soft computing have amazingly evolved in this area in the last few years. Numerous soft computing applications can be found in the field of renewable energy and energy efficiency where soft computing techniques are showing great potential to solve the problems that arise in this area.
The post Top 10 Soft Computing Applications that Businesses Should be Aware appeared first on Analytics Insight.
