Qiong Wang^*, Xiaokan Wang

Journal on Internet of Things, Vol.2, No.2, pp. 75-80, 2020, DOI:10.32604/jiot.2020.010226

Abstract The heating technological requirement of the conventional PID control is difficult to guarantee which based on the precise mathematical model, because the heating furnace for heating treatment with the big inertia, the pure time delay and nonlinear time-varying. Proposed one kind optimized variable method of PID controller based on the genetic algorithm with improved BP network that better realized the completely automatic intelligent control of the entire thermal process than the classics critical purporting (Z-N) method. A heating furnace for the object was simulated with MATLAB, simulation results show that the control system has the quicker response characteristic, the better… More >

Ridvan Saraçoğlu^*, Ahmet Fatih Kazankaya^†

Computer Systems Science and Engineering, Vol.35, No.1, pp. 13-19, 2020, DOI:10.32604/csse.2020.35.013

Abstract The genetic algorithm (GA) is a metaheuristic method which simulates the life cycle and the survival of the fittest in the nature for solving optimization problems. This study aimed to develop enhanced operation by modifying the current GA. This development process includes an adaptation method that contains certain developments and adds a new process to the classic algorithm. Individuals of a population will be trialed to adapt to the current solution of the problem by taking them separately for each generation. With this adaptation method, it is more likely to get better results in a shorter time. Experimental results show… More >

Fu-I Chou¹, Wen-Hsien Ho^2,3, Chiu-Hung Chen^4,*

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 501-512, 2020, DOI:10.32604/iasc.2020.013926

Abstract This paper proposes a novel genetic algorithm (GA) that embeds a niche competition strategy (NCS) in the evolutionary flow to solve the combinational optimization problems that involve multiple loci in the search space. Unlike other niche-information based algorithms, the proposed NCSGA does not need prior knowledge to design niche parameters in the niching phase. To verify the solution capability of the new method, benchmark studies on both the travelling salesman problem (TSP) and the airline recovery scheduling problem were first made. Then, the proposed method was used to solve single nucleotide polymorphism (SNP) barcodes generation problems in a genetic association… More >

Abayomi-Alli A.¹, Misra S.^2,3, Fernández-Sanz L.⁴, Abayomi-Alli O.^2,*, Edun A. R.¹

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 385-396, 2020, DOI:10.32604/iasc.2020.013915

Abstract University timetable scheduling is a complicated constraint problem because educational institutions use timetables to maximize and optimize scarce resources, such as time and space. In this paper, an examination timetable system using Genetic Algorithm and Tabu Search memory with course sandwiching (GAT_CS), was developed for a large public University. The concept of Genetic Algorithm with Selection and Evaluation was implemented while the memory properties of Tabu Search and course sandwiching replaced Crossover and Mutation. The result showed that GAT_CS had hall allocation accuracies of 96.07% and 99.02%, unallocated score of 3.93% and 0.98% for first and second semesters, respectively. It… More >

Iftikhar Ahmad^{1, *}, Rayan Atteah Alsemmeari¹

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1097-1111, 2020, DOI:10.32604/cmc.2020.011732

Abstract An IDS (intrusion detection system) provides a foremost front line mechanism to guard networks, systems, data, and information. That’s why intrusion detection has grown as an active study area and provides significant contribution to cyber-security techniques. Multiple techniques have been in use but major concern in their implementation is variation in their detection performance. The performance of IDS lies in the accurate detection of attacks, and this accuracy can be raised by improving the recognition rate and significant reduction in the false alarms rate. To overcome this problem many researchers have used different machine learning techniques. These techniques have limitations… More >

Win-Chin Lin^a, Chin-Chia Wu^a, Kejian Yu^b, Yong-Han Zhuang^a, Shang-Chia Liu^c

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 671-681, 2018, DOI:10.1080/10798587.2017.1302711

Abstract Most research studies on scheduling problems assume that a job visits certain machines only one time. However, this assumption is invalid in some real-life situations. For example, a job may be processed by the same machine more than once in semiconductor wafer manufacturing or in a printed circuit board manufacturing machine. Such a setting is known as the “re-entrant flowshop”. On the other hand, the importance of learning effect present in many practical situations such as machine shop, in different branches of industry and for a variety of corporate activities, in shortening life cycles, and in an increasing diversity of… More >

Laith Sawaqed¹, Khaled S. Hatamleh^1,2, Mohammad A. Jaradat^1,2, Qais Khasawneh^1,3

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 507-515, 2018, DOI:10.31209/2018.100000039

Abstract Over the past few years, there has been a growing demand to develop efficient precision mechanisms for fine moving applications. Therefore, several piezoelectric driven mechanisms have been proposed for such applications. In this work an optimal synthesis of a four-bar mechanism with three PEAs is proposed. Two evolutionary multi-objective Genetic Algorithms (GAs) are formulated and applied; A Genetic Algorithm Synthesis method (GAS) is first used to obtain a synthesis solution for the mechanism regardless of power consumption. Then another Genetic Algorithm Minimum Power Synthesis method (GAMPS) is used to obtain the synthesis solution of minimum power consumption. For that purpose,… More >

Imed Kacem, Ahmed Kadri, Pierre Laroche

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 421-430, 2018, DOI:10.31209/2018.100000016

Abstract This paper addresses an inventory regulation problem in bicycle sharingsystems. The problem is to balance a network consisting of a set of stations by using a single vehicle, with the aim of minimizing the weighted sum of the waiting times during which some stations remain imbalanced. Motivated by the complexity of this problem, we propose a two-stage procedure based on decomposition. First, the network is divided into multiple zones by using two different clustering strategies. Then, the balancing problem is solved in each zone. Finally, the order in which the zones must be visited is defined. To solve these problems,… More >

Qais A. Khasawneh^1,3, Mohammad Abdel Kareem Jaradat^1,2, Mohammad Al-Shabi⁴, Hala Khalaf¹

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 443-457, 2018, DOI:10.31209/2018.100000008

Abstract This work presents a new micro-positioning system that is implemented in an inchworm robot to move into desired locations. The system consists of four-bar mechanism; one link is fixed, and each one of the remaining links carries a piezoelectric actuator (PZT). PZTs are specifically chosen since they provide fast response and small displacements; up to ±30 µm for ±100 Volts. The system’s mathematical model is derived and is numerically simulated by MATLAB. Three fuzzy PI controllers, which are tuned automatically by genetic algorithm, are designed to control the system. Results indicate an error of less than 1% although disturbances present. More >

Mohammed Algabri^a,c, Mohamed Abdelkader Bencherif^c, Mansour Alsulaiman^b,c, Ghulam Muhammad^b, Mohamed Amine Mekhtiche^c

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 267-274, 2018, DOI:10.1080/10798587.2017.1278961

Abstract A method that uses fuzzy logic to classify two simple speech features for the automatic classification of voiced and unvoiced phonemes is proposed. In addition, two variants, in which soft computing techniques are used to enhance the performance of fuzzy logic by tuning the parameters of the membership functions, are also presented. The three methods, manually constructed fuzzy logic (VUFL), fuzzy logic optimized with genetic algorithm (VUFL-GA), and fuzzy logic with optimized particle swarm optimization (VUFL-PSO), are implemented and then evaluated using the TIMIT speech corpus. Performance is evaluated using the TIMIT database in both clean and noisy environments. Four… More >